Daniel L. Rubin

243 papers A* 4A 3B 4C 1Misc 33Journal 160Unranked 38

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Weakly supervised language models for automated extraction of critical findings from radiology reports. npj Digit. Medicine Avisha Das, Ish A. Talati, Juan Manuel Zambrano Chaves, Daniel L. Rubin, Imon Banerjee
2024	—	`conf`	Addressing Catastrophic Forgetting by Modulating Global Batch Normalization Statistics for Medical Domain Expansion. AIPAD/PILM@MICCAI Sharut Gupta, Ken Chang, Liangqiong Qu, Aakanksha Rana, Syed Rakin Ahmed, Mehak Aggarwal, Nishanth Thumbavanam Arun, Ashwin Vaswani, Shruti Raghavan, Vibha Agarwal, Mishka Gidwani, Katharina Hoebel, Jay B. Patel, Charles Lu, Christopher P. Bridge, Daniel L. Rubin, Jayashree Kalpathy-Cramer, Praveer Singh
2024	J	`jnl`	An Explainable and Actionable Mistrust Scoring Framework for Model Monitoring. IEEE Trans. Artif. Intell. Nandita Bhaskhar, Daniel L. Rubin, Christopher Lee-Messer
2024	J	`jnl`	Mirrored X-Net: Joint classification and contrastive learning for weakly supervised GA segmentation in SD-OCT. Pattern Recognit. Zexuan Ji, Xiao Ma, Theodore Leng, Daniel L. Rubin, Qiang Chen
2024	J	`jnl`	Privacy preservation for federated learning in health care. Patterns Sarthak Pati, Sourav Kumar, Amokh Varma, Brandon Edwards, Charles Lu, Liangqiong Qu, Justin J. Wang, Anantharaman Lakshminarayanan, Shih-han Wang, Micah J. Sheller, Ken Chang, Praveer Singh, Daniel L. Rubin, Jayashree Kalpathy-Cramer, Spyridon Bakas
2024	J	`jnl`	Towards trustworthy seizure onset detection using workflow notes. npj Digit. Medicine Khaled Saab, Siyi Tang, Mohamed Taha, Christopher Lee-Messer, Christopher Ré, Daniel L. Rubin
2023	A	`conf`	ATCON: Attention Consistency for Vision Models. WACV Ali Mirzazadeh, Florian Dubost, Maxwell Pike, Krish Maniar, Max Zuo, Christopher Lee-Messer, Daniel L. Rubin
2023	J	`jnl`	Clinical outcome prediction using observational supervision with electronic health records and audit logs. J. Biomed. Informatics Nandita Bhaskhar, Wui Ip, Jonathan H. Chen, Daniel L. Rubin
2023	—	`conf`	Exploring Image Augmentations for Siamese Representation Learning with Chest X-Rays. MIDL Rogier van der Sluijs, Nandita Bhaskhar, Daniel L. Rubin, Curtis P. Langlotz, Akshay S. Chaudhari
2023	J	`jnl`	Exploring Image Augmentations for Siamese Representation Learning with Chest X-Rays. CoRR Rogier van der Sluijs, Nandita Bhaskhar, Daniel L. Rubin, Curtis P. Langlotz, Akshay Chaudhari
2023	—	`conf`	Graph-Based Fusion of Imaging and Non-Imaging Data for Disease Trajectory Prediction. NER Amara Tariq, Siyi Tang, Hifza Sakhi, Leo Anthony Celi, Janice M. Newsome, Daniel L. Rubin, Hari Trivedi, Judy Gichoya, Bhavik N. Patel, Imon Banerjee
2023	J	`jnl`	Label-Efficient Self-Supervised Federated Learning for Tackling Data Heterogeneity in Medical Imaging. IEEE Trans. Medical Imaging Rui Yan, Liangqiong Qu, Qingyue Wei, Shih-Cheng Huang, Liyue Shen, Daniel L. Rubin, Lei Xing, Yuyin Zhou
2023	—	`conf`	Modeling Multivariate Biosignals With Graph Neural Networks and Structured State Space Models. CHIL Siyi Tang, Jared A. Dunnmon, Liangqiong Qu, Khaled Kamal Saab, Tina Baykaner, Christopher Lee-Messer, Daniel L. Rubin
2023	J	`jnl`	PlexusNet: A neural network architectural concept for medical image classification. Comput. Biol. Medicine Okyaz Eminaga, Mahmoud Abbas, Jeanne Shen, Mark A. Laurie, James D. Brooks, Joseph C. Liao, Daniel L. Rubin
2023	J	`jnl`	Predicting 30-Day All-Cause Hospital Readmission Using Multimodal Spatiotemporal Graph Neural Networks. IEEE J. Biomed. Health Informatics Siyi Tang, Amara Tariq, Jared A. Dunnmon, Umesh Sharma, Praneetha Elugunti, Daniel L. Rubin, Bhavik N. Patel, Imon Banerjee
2023	A*	`conf`	RaLEs: a Benchmark for Radiology Language Evaluations. NeurIPS Juanma Zambrano Chaves, Nandita Bhaskhar, Maayane Attias, Jean-Benoit Delbrouck, Daniel L. Rubin, Andreas M. Loening, Curtis P. Langlotz, Akshay Chaudhari
2023	A	`conf`	Semi-Supervised Learning for Sparsely-Labeled Sequential Data: Application to Healthcare Video Processing. WACV Florian Dubost, Erin Hong, Siyi Tang, Nandita Bhaskhar, Christopher Lee-Messer, Daniel L. Rubin
2023	J	`jnl`	Towards trustworthy seizure onset detection using workflow notes. CoRR Khaled Saab, Siyi Tang, Mohamed Taha, Christopher Lee-Messer, Christopher Ré, Daniel L. Rubin
2022	J	`jnl`	2.5D and 3D segmentation of brain metastases with deep learning on multinational MRI data. Frontiers Neuroinformatics Jon André Ottesen, Darvin Yi, Elizabeth Tong, Michael Iv, Anna Latysheva, Cathrine Saxhaug, Kari Dolven Jacobsen, Åslaug Helland, Kyrre Eeg Emblem, Daniel L. Rubin, Atle Bjørnerud, Greg Zaharchuk, Endre Grøvik
2022	J	`jnl`	A weakly supervised model for the automated detection of adverse events using clinical notes. J. Biomed. Informatics Josh Sanyal, Daniel L. Rubin, Imon Banerjee
2022	J	`jnl`	ATCON: Attention Consistency for Vision Models. CoRR Ali Mirzazadeh, Florian Dubost, Maxwell Pike, Krish Maniar, Max Zuo, Christopher Lee-Messer, Daniel L. Rubin
2022	J	`jnl`	Author Correction: Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence. Nat. Mach. Intell. Xiang Bai, Hanchen Wang, Liya Ma, Yongchao Xu, Jiefeng Gan, Ziwei Fan, Fan Yang, Ke Ma, Jiehua Yang, Song Bai, Chang Shu, Xinyu Zou, Renhao Huang, Changzheng Zhang, Xiaowu Liu, Dandan Tu, Chuou Xu, Wenqing Zhang, Xi Wang, Anguo Chen, Yu Zeng, Dehua Yang, Ming-Wei Wang, Nagaraj Holalkere, Neil J. Halin, Ihab R. Kamel, Jia Wu, Xuehua Peng, Xiang Wang, Jianbo Shao, Pattanasak Mongkolwat, Jianjun Zhang, Weiyang Liu, Michael Roberts, Zhongzhao Teng, Lucian Beer, Lorena Escudero Sanchez, Evis Sala, Daniel L. Rubin, Adrian Weller, Joan Lasenby, Chuansheng Zheng, Jianming Wang, Zhen Li, Carola Schönlieb, Tian Xia
2022	J	`jnl`	Automating Scoliosis Measurements in Radiographic Studies with Machine Learning: Comparing Artificial Intelligence and Clinical Reports. J. Digit. Imaging Audrey Ha, Bao H. Do, Adam L. Bartret, Charles X. Fang, Albert Hsiao, Amelie M. Lutz, Imon Banerjee, Geoffrey M. Riley, Daniel L. Rubin, Kathryn J. Stevens, Erin Wang, Shannon Wang, Christopher F. Beaulieu, Brian Hurt
2022	J	`jnl`	Contrastive learning-based pretraining improves representation and transferability of diabetic retinopathy classification models. CoRR Minhaj Nur Alam, Rikiya Yamashita, Vignav Ramesh, Tejas S. Prabhune, Jennifer I. Lim, R. V. P. Chan, Joelle A. Hallak, Theodore Leng, Daniel L. Rubin
2022	Misc	`conf`	Graph-based Fusion Modeling and Explanation for Disease Trajectory Prediction. AMIA Amara Tariq, Siyi Tang, Hifza Sakhi, Leo Anthony Celi, Janice M. Newsome, Daniel L. Rubin, Hari Trivedi, Judy Gichoya, Bhavik N. Patel, Imon Banerjee
2022	J	`jnl`	Label-Efficient Self-Supervised Federated Learning for Tackling Data Heterogeneity in Medical Imaging. CoRR Rui Yan, Liangqiong Qu, Qingyue Wei, Shih-Cheng Huang, Liyue Shen, Daniel L. Rubin, Lei Xing, Yuyin Zhou
2022	J	`jnl`	Masked Co-attentional Transformer reconstructs 100x ultra-fast/low-dose whole-body PET from longitudinal images and anatomically guided MRI. CoRR Yan-Ran Wang, Liangqiong Qu, Natasha Diba Sheybani, Xiaolong Luo, Jiangshan Wang, Kristina Elizabeth Hawk, Ashok Joseph Theruvath, Sergios Gatidis, Xuerong Xiao, Allison Pribnow, Daniel L. Rubin, Heike E. Daldrup-Link
2022	J	`jnl`	Multimodal spatiotemporal graph neural networks for improved prediction of 30-day all-cause hospital readmission. CoRR Siyi Tang, Amara Tariq, Jared Dunnmon, Umesh Sharma, Praneetha Elugunti, Daniel L. Rubin, Bhavik N. Patel, Imon Banerjee
2022	—	`conf`	Opportunistic Incidence Prediction of Multiple Chronic Diseases from Abdominal CT Imaging Using Multi-task Learning. MICCAI (8) Louis Blankemeier, Isabel Gallegos, Juan Manuel Zambrano Chaves, David J. Maron, Alexander T. Sandhu, Fátima Rodriguez, Daniel L. Rubin, Bhavik N. Patel, Marc H. Willis, Robert D. Boutin, Akshay S. Chaudhari
2022	—	`conf`	Reducing Reliance on Spurious Features in Medical Image Classification with Spatial Specificity. MLHC Khaled Saab, Sarah M. Hooper, Mayee F. Chen, Michael Zhang, Daniel L. Rubin, Christopher Ré
2022	A*	`conf`	Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning. CVPR Liangqiong Qu, Yuyin Zhou, Paul Pu Liang, Yingda Xia, Feifei Wang, Ehsan Adeli, Li Fei-Fei, Daniel L. Rubin
2022	A*	`conf`	Self-Supervised Graph Neural Networks for Improved Electroencephalographic Seizure Analysis. ICLR Siyi Tang, Jared Dunnmon, Khaled Kamal Saab, Xuan Zhang, Qianying Huang, Florian Dubost, Daniel L. Rubin, Christopher Lee-Messer
2022	—	`conf`	Self-attention Capsule Network for Tissue Classification in Case of Challenging Medical Image Statistics. ECCV Workshops (3) Assaf Hoogi, Brian Wilcox, Yachee Gupta, Daniel L. Rubin
2022	J	`jnl`	Spatiotemporal Modeling of Multivariate Signals With Graph Neural Networks and Structured State Space Models. CoRR Siyi Tang, Jared A. Dunnmon, Liangqiong Qu, Khaled Kamal Saab, Christopher Lee-Messer, Daniel L. Rubin
2022	J	`jnl`	SplitAVG: A Heterogeneity-Aware Federated Deep Learning Method for Medical Imaging. IEEE J. Biomed. Health Informatics Miao Zhang, Liangqiong Qu, Praveer Singh, Jayashree Kalpathy-Cramer, Daniel L. Rubin
2022	J	`jnl`	Supervised Machine Learning Algorithm for Detecting Consistency between Reported Findings and the Conclusions of Mammography Reports. CoRR Alexander S. Berdichevsky, Mor Peleg, Daniel L. Rubin
2022	J	`jnl`	TRUST-LAPSE: An Explainable & Actionable Mistrust Scoring Framework for Model Monitoring. CoRR Nandita Bhaskhar, Daniel L. Rubin, Christopher Lee-Messer
2022	J	`jnl`	The Importance of Background Information for Out of Distribution Generalization. CoRR Jupinder Parmar, Khaled Saab, Brian Pogatchnik, Daniel L. Rubin, Christopher Ré
2022	J	`jnl`	Transfer language space with similar domain adaptation: a case study with hepatocellular carcinoma. J. Biomed. Semant. Amara Tariq, Omar Kallas, Patricia C. Balthazar, Scott Jeffery Lee, Terry Desser, Daniel L. Rubin, Judy Wawira Gichoya, Imon Banerjee
2021	Misc	`conf`	A Fusion NLP Model for the Inference of Standardized Thyroid Nodule Malignancy Scores from Radiology Report Text. AMIA Thiago Santos, Omar Kallas, Janice M. Newsome, Daniel L. Rubin, Judy W. Gichoya, Imon Banerjee
2021	J	`jnl`	Addressing catastrophic forgetting for medical domain expansion. CoRR Sharut Gupta, Praveer Singh, Ken Chang, Liangqiong Qu, Mehak Aggarwal, Nishanth Thumbavanam Arun, Ashwin Vaswani, Shruti Raghavan, Vibha Agarwal, Mishka Gidwani, Katharina Hoebel, Jay B. Patel, Charles Lu, Christopher P. Bridge, Daniel L. Rubin, Jayashree Kalpathy-Cramer
2021	J	`jnl`	Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence. CoRR Xiang Bai, Hanchen Wang, Liya Ma, Yongchao Xu, Jiefeng Gan, Ziwei Fan, Fan Yang, Ke Ma, Jiehua Yang, Song Bai, Chang Shu, Xinyu Zou, Renhao Huang, Changzheng Zhang, Xiaowu Liu, Dandan Tu, Chuou Xu, Wenqing Zhang, Xi Wang, Anguo Chen, Yu Zeng, Dehua Yang, Ming-Wei Wang, Nagaraj Holalkere, Neil J. Halin, Ihab R. Kamel, Jia Wu, Xuehua Peng, Xiang Wang, Jianbo Shao, Pattanasak Mongkolwat, Jianjun Zhang, Weiyang Liu, Michael Roberts, Zhongzhao Teng, Lucian Beer, Lorena Escudero Sanchez, Evis Sala, Daniel L. Rubin, Adrian Weller, Joan Lasenby, Chuangsheng Zheng, Jianming Wang, Zhen Li, Carola-Bibiane Schönlieb, Tian Xia
2021	J	`jnl`	Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence. Nat. Mach. Intell. Xiang Bai, Hanchen Wang, Liya Ma, Yongchao Xu, Jiefeng Gan, Ziwei Fan, Fan Yang, Ke Ma, Jiehua Yang, Song Bai, Chang Shu, Xinyu Zou, Renhao Huang, Changzheng Zhang, Xiaowu Liu, Dandan Tu, Chuou Xu, Wenqing Zhang, Xi Wang, Anguo Chen, Yu Zeng, Dehua Yang, Ming-Wei Wang, Nagaraj Holalkere, Neil J. Halin, Ihab R. Kamel, Jia Wu, Xuehua Peng, Xiang Wang, Jianbo Shao, Pattanasak Mongkolwat, Jianjun Zhang, Weiyang Liu, Michael Roberts, Zhongzhao Teng, Lucian Beer, Lorena Escudero Sanchez, Evis Sala, Daniel L. Rubin, Adrian Weller, Joan Lasenby, Chuansheng Zheng, Jianming Wang, Zhen Li, Carola Schönlieb, Tian Xia
2021	J	`jnl`	An Experimental Study of Data Heterogeneity in Federated Learning Methods for Medical Imaging. CoRR Liangqiong Qu, Niranjan Balachandar, Daniel L. Rubin
2021	J	`jnl`	An integrated time adaptive geographic atrophy prediction model for SD-OCT images. Medical Image Anal. Yuhan Zhang, Xiwei Zhang, Zexuan Ji, Sijie Niu, Theodore Leng, Daniel L. Rubin, Songtao Yuan, Qiang Chen
2021	J	`jnl`	Automated Detection of Patients in Hospital Video Recordings. CoRR Siddharth Sharma, Florian Dubost, Christopher Lee-Messer, Daniel L. Rubin
2021	J	`jnl`	Automated Seizure Detection and Seizure Type Classification From Electroencephalography With a Graph Neural Network and Self-Supervised Pre-Training. CoRR Siyi Tang, Jared A. Dunnmon, Khaled Saab, Xuan Zhang, Qianying Huang, Florian Dubost, Daniel L. Rubin, Christopher Lee-Messer
2021	J	`jnl`	COVID-19 Lung Lesion Segmentation Using a Sparsely Supervised Mask R-CNN on Chest X-rays Automatically Computed from Volumetric CTs. CoRR Vignav Ramesh, Blaine Rister, Daniel L. Rubin
2021	J	`jnl`	Comparison of segmentation-free and segmentation-dependent computer-aided diagnosis of breast masses on a public mammography dataset. J. Biomed. Informatics Rebecca Sawyer Lee, Jared A. Dunnmon, Ann He, Siyi Tang, Christopher Ré, Daniel L. Rubin
2021	J	`jnl`	Double Descent Optimization Pattern and Aliasing: Caveats of Noisy Labels. CoRR Florian Dubost, Khaled Kamal Saab, Erin Hong, Daniel Yang Fu, Max Pike, Siddharth Sharma, Siyi Tang, Nandita Bhaskhar, Christopher Lee-Messer, Daniel L. Rubin
2021	J	`jnl`	Handling Data Heterogeneity with Generative Replay in Collaborative Learning for Medical Imaging. CoRR Liangqiong Qu, Niranjan Balachandar, Miao Zhang, Daniel L. Rubin
2021	J	`jnl`	Handling missing MRI sequences in deep learning segmentation of brain metastases: a multicenter study. npj Digit. Medicine Endre Grøvik, Darvin Yi, Michael Iv, Elizabeth Tong, Line Brennhaug Nilsen, Anna Latysheva, Cathrine Saxhaug, Kari Dolven Jacobsen, Åslaug Helland, Kyrre Eeg Emblem, Daniel L. Rubin, Greg Zaharchuk
2021	J	`jnl`	Learning Domain-Agnostic Visual Representation for Computational Pathology Using Medically-Irrelevant Style Transfer Augmentation. IEEE Trans. Medical Imaging Rikiya Yamashita, Jin Long, Snikitha Banda, Jeanne Shen, Daniel L. Rubin
2021	J	`jnl`	Learning domain-agnostic visual representation for computational pathology using medically-irrelevant style transfer augmentation. CoRR Rikiya Yamashita, Jin Long, Snikitha Banda, Jeanne Shen, Daniel L. Rubin
2021	—	`conf`	Observational Supervision for Medical Image Classification Using Gaze Data. MICCAI (2) Khaled Saab, Sarah M. Hooper, Nimit Sharad Sohoni, Jupinder Parmar, Brian Pogatchnik, Sen Wu, Jared A. Dunnmon, Hongyang R. Zhang, Daniel L. Rubin, Christopher Ré
2021	—	`conf`	Out of Distribution Detection for Medical Images. UNSURE/PIPPI@MICCAI Oliver Zhang, Jean-Benoit Delbrouck, Daniel L. Rubin
2021	—	`conf`	QIAI at MEDIQA 2021: Multimodal Radiology Report Summarization. BioNLP@NAACL-HLT Jean-Benoit Delbrouck, Cassie Zhang, Daniel L. Rubin
2021	J	`jnl`	RadFusion: Benchmarking Performance and Fairness for Multimodal Pulmonary Embolism Detection from CT and EHR. CoRR Yuyin Zhou, Shih-Cheng Huang, Jason Alan Fries, Alaa Youssef, Timothy J. Amrhein, Marcello Chang, Imon Banerjee, Daniel L. Rubin, Lei Xing, Nigam Shah, Matthew P. Lungren
2021	J	`jnl`	Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning. CoRR Liangqiong Qu, Yuyin Zhou, Paul Pu Liang, Yingda Xia, Feifei Wang, Li Fei-Fei, Ehsan Adeli, Daniel L. Rubin
2021	J	`jnl`	SplitAVG: A heterogeneity-aware federated deep learning method for medical imaging. CoRR Miao Zhang, Liangqiong Qu, Praveer Singh, Jayashree Kalpathy-Cramer, Daniel L. Rubin
2020	J	`jnl`	Accounting for data variability in multi-institutional distributed deep learning for medical imaging. J. Am. Medical Informatics Assoc. Niranjan Balachandar, Ken Chang, Jayashree Kalpathy-Cramer, Daniel L. Rubin
2020	J	`jnl`	Advancing Semantic Interoperability of Image Annotations: Automated Conversion of Non-standard Image Annotations in a Commercial PACS to the Annotation and Image Markup. J. Digit. Imaging Nathaniel C. Swinburne, David S. Mendelson, Daniel L. Rubin
2020	J	`jnl`	Automatic Staging of Cancer Tumors Using AIM Image Annotations and Ontologies. J. Digit. Imaging Edson F. Luque, Nelson J. O. Miranda, Daniel L. Rubin, Dilvan A. Moreira
2020	—	`conf`	Brain Metastasis Segmentation Network Trained with Robustness to Annotations with Multiple False Negatives. MIDL Darvin Yi, Endre Grøvik, Michael Iv, Elizabeth Tong, Greg Zaharchuk, Daniel L. Rubin
2020	J	`jnl`	Brain Metastasis Segmentation Network Trained with Robustness to Annotations with Multiple False Negatives. CoRR Darvin Yi, Endre Grøvik, Michael Iv, Elizabeth Tong, Greg Zaharchuk, Daniel L. Rubin
2020	A*	`conf`	Cancer Treatment Classification with Electronic Medical Health Records (Student Abstract). AAAI Jiaming Zeng, Imon Banerjee, Michael Francis Gensheimer, Daniel L. Rubin
2020	J	`jnl`	Corrigendum to: Accounting for data variability in multi-institutional distributed deep learning for medical imaging. J. Am. Medical Informatics Assoc. Niranjan Balachandar, Ken Chang, Jayashree Kalpathy-Cramer, Daniel L. Rubin
2020	J	`jnl`	Cross-Modal Data Programming Enables Rapid Medical Machine Learning. Patterns Jared A. Dunnmon, Alexander J. Ratner, Khaled Saab, Nishith Khandwala, Matthew Markert, Hersh Sagreiya, Roger E. Goldman, Christopher Lee-Messer, Matthew P. Lungren, Daniel L. Rubin, Christopher Ré
2020	J	`jnl`	Data Valuation for Medical Imaging Using Shapley Value: Application on A Large-scale Chest X-ray Dataset. CoRR Siyi Tang, Amirata Ghorbani, Rikiya Yamashita, Sameer Rehman, Jared A. Dunnmon, James Y. Zou, Daniel L. Rubin
2020	—	`conf`	Federated Learning for Breast Density Classification: A Real-World Implementation. DART/DCL@MICCAI Holger R. Roth, Ken Chang, Praveer Singh, Nir Neumark, Wenqi Li, Vikash Gupta, Sharut Gupta, Liangqiong Qu, Alvin Ihsani, Bernardo C. Bizzo, Yuhong Wen, Varun Buch, Meesam Shah, Felipe Kitamura, Matheus Mendonça, Vitor Lavor, Ahmed Harouni, Colin Compas, Jesse Tetreault, Prerna Dogra, Yan Cheng, Selnur Erdal, Richard D. White, Behrooz Hashemian, Thomas J. Schultz, Miao Zhang, Adam McCarthy, B. Min Yun, Elshaimaa Sharaf, Katharina Viktoria Hoebel, Jay B. Patel, Bryan Chen, Sean Ko, Evan Leibovitz, Etta D. Pisano, Laura Coombs, Daguang Xu, Keith J. Dreyer, Ittai Dayan, Ram C. Naidu, Mona Flores, Daniel L. Rubin, Jayashree Kalpathy-Cramer
2020	J	`jnl`	Federated Learning for Breast Density Classification: A Real-World Implementation. CoRR Holger R. Roth, Ken Chang, Praveer Singh, Nir Neumark, Wenqi Li, Vikash Gupta, Sharut Gupta, Liangqiong Qu, Alvin Ihsani, Bernardo C. Bizzo, Yuhong Wen, Varun Buch, Meesam Shah, Felipe Kitamura, Matheus Mendonça, Vitor Lavor, Ahmed Harouni, Colin Compas, Jesse Tetreault, Prerna Dogra, Yan Cheng, Selnur Erdal, Richard D. White, Behrooz Hashemian, Thomas J. Schultz, Miao Zhang, Adam McCarthy, B. Min Yun, Elshaimaa Sharaf, Katharina Viktoria Hoebel, Jay B. Patel, Bryan Chen, Sean Ko, Evan Leibovitz, Etta D. Pisano, Laura Coombs, Daguang Xu, Keith J. Dreyer, Ittai Dayan, Ram C. Naidu, Mona Flores, Daniel L. Rubin, Jayashree Kalpathy-Cramer
2020	J	`jnl`	Let's Hope it Works! Inaccurate Supervision of Neural Networks with Incorrect Labels: Application to Epilepsy. CoRR Florian Dubost, Erin Hong, Daniel Y. Fu, Nandita Bhaskhar, Siyi Tang, Khaled Saab, Daniel L. Rubin, Jared Dunnmon, Christopher Lee-Messer
2020	J	`jnl`	MS-CAM: Multi-Scale Class Activation Maps for Weakly-Supervised Segmentation of Geographic Atrophy Lesions in SD-OCT Images. IEEE J. Biomed. Health Informatics Xiao Ma, Zexuan Ji, Sijie Niu, Theodore Leng, Daniel L. Rubin, Qiang Chen
2020	J	`jnl`	Natural Language Generation Model for Mammography Reports Simulation. IEEE J. Biomed. Health Informatics Assaf Hoogi, Arjun Mishra, Francisco Gimenez, Jeffrey Dong, Daniel L. Rubin
2020	J	`jnl`	Probabilistic bounds on data sensitivity in deep rectifier networks. CoRR Blaine Rister, Daniel L. Rubin
2020	J	`jnl`	Random Bundle: Brain Metastases Segmentation Ensembling through Annotation Randomization. CoRR Darvin Yi, Endre Grøvik, Michael Iv, Elizabeth Tong, Greg Zaharchuk, Daniel L. Rubin
2020	J	`jnl`	The unreasonable effectiveness of Batch-Norm statistics in addressing catastrophic forgetting across medical institutions. CoRR Sharut Gupta, Praveer Singh, Ken Chang, Mehak Aggarwal, Nishanth Thumbavanam Arun, Liangqiong Qu, Katharina Hoebel, Jay B. Patel, Mishka Gidwani, Ashwin Vaswani, Daniel L. Rubin, Jayashree Kalpathy-Cramer
2020	J	`jnl`	Toward Data-Driven Learning Healthcare Systems in Interventional Radiology: Implementation to Evaluate Venous Stent Patency. J. Digit. Imaging David M. Cohn, Tarub S. Mabud, Victoria A. Arendt, Andre D. Souffrant, Gyeong S. Jeon, Xiao An, William T. Kuo, Daniel Y. Sze, Lawrence V. Hofmann, Daniel L. Rubin
2020	J	`jnl`	Weak supervision as an efficient approach for automated seizure detection in electroencephalography. npj Digit. Medicine Khaled Saab, Jared Dunnmon, Christopher Ré, Daniel L. Rubin, Christopher Lee-Messer
2019	J	`jnl`	A Deep-learning Approach for Prognosis of Age-Related Macular Degeneration Disease using SD-OCT Imaging Biomarkers. CoRR Imon Banerjee, Luis de Sisternes, Joelle A. Hallak, Theodore Leng, Aaron Osborne, Mary Durbin, Daniel L. Rubin
2019	—	`conf`	A Multi-Scale Deep Convolutional Neural Network For Joint Segmentation And Prediction Of Geographic Atrophy In SD-OCT Images. ISBI Yuhan Zhang, Zexuan Ji, Sijie Niu, Theodore Leng, Daniel L. Rubin, Qiang Chen
2019	—	`conf`	A lung graph model for the classification of interstitial lung diseases on CT images. Computer-Aided Diagnosis Guillaume Vanoost, Yashin Dicente Cid, Daniel L. Rubin, Adrien Depeursinge
2019	J	`jnl`	Automated Detection of Measurements and Their Descriptors in Radiology Reports Using a Hybrid Natural Language Processing Algorithm. J. Digit. Imaging Selen Bozkurt, Emel Alkim, Imon Banerjee, Daniel L. Rubin
2019	J	`jnl`	Automated geographic atrophy segmentation for SD-OCT images based on two-stage learning model. Comput. Biol. Medicine Rongbin Xu, Sijie Niu, Qiang Chen, Zexuan Ji, Daniel L. Rubin, Yuehui Chen
2019	J	`jnl`	Automatic inference of BI-RADS final assessment categories from narrative mammography report findings. J. Biomed. Informatics Imon Banerjee, Selen Bozkurt, Emel Alkim, Hersh Sagreiya, Allison W. Kurian, Daniel L. Rubin
2019	J	`jnl`	Biologic and Prognostic Feature Scores from Whole-Slide Histology Images Using Deep Learning. CoRR Okyaz Eminaga, Mahmoud Abbas, Yuri Tolkach, Rosalie Nolley, Christian Kunder, Axel Semjonow, Martin Boegemann, Andreas M. Loening, James D. Brooks, Daniel L. Rubin
2019	J	`jnl`	Comparative effectiveness of convolutional neural network (CNN) and recurrent neural network (RNN) architectures for radiology text report classification. Artif. Intell. Medicine Imon Banerjee, Yuan Ling, Matthew C. Chen, Sadid A. Hasan, Curtis P. Langlotz, Nathaniel Moradzadeh, Brian E. Chapman, Timothy Amrhein, David A. Mong, Daniel L. Rubin, Oladimeji Farri, Matthew P. Lungren
2019	J	`jnl`	Cross-Modal Data Programming Enables Rapid Medical Machine Learning. CoRR Jared Dunnmon, Alexander Ratner, Nishith Khandwala, Khaled Saab, Matthew Markert, Hersh Sagreiya, Roger E. Goldman, Christopher Lee-Messer, Matthew P. Lungren, Daniel L. Rubin, Christopher Ré
2019	—	`conf`	Deep Active Lesion Segmentation. MLMI@MICCAI Ali Hatamizadeh, Assaf Hoogi, Debleena Sengupta, Wuyue Lu, Brian Wilcox, Daniel L. Rubin, Demetri Terzopoulos
2019	J	`jnl`	Deep Active Lesion Segmentation. CoRR Ali Hatamizadeh, Assaf Hoogi, Debleena Sengupta, Wuyue Lu, Brian Wilcox, Daniel L. Rubin, Demetri Terzopoulos
2019	J	`jnl`	Deep Learning Enables Automatic Detection and Segmentation of Brain Metastases on Multi-Sequence MRI. CoRR Endre Grøvik, Darvin Yi, Michael Iv, Elisabeth Tong, Daniel L. Rubin, Greg Zaharchuk
2019	J	`jnl`	Deep Learning for Prostate Pathology. CoRR Okyaz Eminaga, Yuri Tolkach, Christian Kunder, Mahmoud Abbas, Ryan Han, Rosalie Nolley, Axel Semjonow, Martin Boegemann, Sebastian Huss, Andreas M. Loening, Robert B. West, Geoffrey A. Sonn, Richard E. Fan, Olaf Bettendorf, James D. Brooks, Daniel L. Rubin
2019	Misc	`conf`	Detecting unanticipated actions downstream from clinical decision support: a data mining approach. AMIA Ron C. Li, Imon Banerjee, Daniel L. Rubin, Jonathan H. Chen
2019	—	`conf`	Doubly Weak Supervision of Deep Learning Models for Head CT. MICCAI (3) Khaled Saab, Jared Dunnmon, Roger E. Goldman, Alexander Ratner, Hersh Sagreiya, Christopher Ré, Daniel L. Rubin
2019	J	`jnl`	Geographic atrophy segmentation in SD-OCT images using synthesized fundus autofluorescence imaging. Comput. Methods Programs Biomed. Menglin Wu, Xinxin Cai, Qiang Chen, Zexuan Ji, Sijie Niu, Theodore Leng, Daniel L. Rubin, Hyunjin Park
2019	J	`jnl`	Handling Missing MRI Input Data in Deep Learning Segmentation of Brain Metastases: A Multi-Center Study. CoRR Endre Grøvik, Darvin Yi, Michael Iv, Elizabeth Tong, Line Brennhaug Nilsen, Anna Latysheva, Cathrine Saxhaug, Kari Dolven Jacobsen, Åslaug Helland, Kyrre Eeg Emblem, Daniel L. Rubin, Greg Zaharchuk
2019	J	`jnl`	MRI Pulse Sequence Integration for Deep-Learning Based Brain Metastasis Segmentation. CoRR Darvin Yi, Endre Grøvik, Michael Iv, Elisabeth Tong, Kyrre Eeg Emblem, Line Brennhaug Nilsen, Cathrine Saxhaug, Anna Latysheva, Kari Dolven Jacobsen, Åslaug Helland, Greg Zaharchuk, Daniel L. Rubin
2019	J	`jnl`	Plexus Convolutional Neural Network (PlexusNet): A novel neural network architecture for histologic image analysis. CoRR Okyaz Eminaga, Mahmoud Abbas, Christian Kunder, Andreas M. Loening, Jeanne Shen, James D. Brooks, Curtis P. Langlotz, Daniel L. Rubin
2019	Misc	`conf`	Prediction of Imaging Outcomes from Electronic Health Records: Pulmonary Embolism Case-Study. AMIA Imon Banerjee, Miji Sofela, Timothy Amrhein, Daniel L. Rubin, Roham Zamanian, Matthew P. Lungren
2019	J	`jnl`	Putting the data before the algorithm in big data addressing personalized healthcare. npj Digit. Medicine Eli M. Cahan, Tina Hernandez-Boussard, Sonoo Thadaney Israni, Daniel L. Rubin
2019	J	`jnl`	Self-Attention Capsule Networks for Image Classification. CoRR Assaf Hoogi, Brian Wilcox, Yachee Gupta, Daniel L. Rubin
2018	—	`conf`	A Multi-scale Multiple Sclerosis Lesion Change Detection in a Multi-sequence MRI. DLMIA/ML-CDS@MICCAI Myra Cheng, Alfiia Galimzianova, Ziga Lesjak, Ziga Spiclin, Christopher B. Lock, Daniel L. Rubin
2018	Misc	`conf`	A Scalable Machine Learning Approach for Inferring Probabilistic US-LI-RADS Categorization. AMIA Imon Banerjee, Hailey H. Choi, Terry S. Desser, Daniel L. Rubin
2018	J	`jnl`	A Scalable Machine Learning Approach for Inferring Probabilistic US-LI-RADS Categorization. CoRR Imon Banerjee, Hailey H. Choi, Terry S. Desser, Daniel L. Rubin
2018	Misc	`conf`	An Automated Feature Engineering for Digital Rectal Examination Documentation using Natural Language Processing. AMIA Selen Bozkurt, Jung Park In, Kathleen Mary Kan, Michelle Ferrari, Daniel L. Rubin, James D. Brooks, Tina Hernandez-Boussard
2018	J	`jnl`	Automatic information extraction from unstructured mammography reports using distributed semantics. J. Biomed. Informatics Anupama Gupta, Imon Banerjee, Daniel L. Rubin
2018	J	`jnl`	CT organ segmentation using GPU data augmentation, unsupervised labels and IOU loss. CoRR Blaine Rister, Darvin Yi, Kaushik Shivakumar, Tomomi Nobashi, Daniel L. Rubin
2018	J	`jnl`	Distributed deep learning networks among institutions for medical imaging. J. Am. Medical Informatics Assoc. Ken Chang, Niranjan Balachandar, Carson K. Lam, Darvin Yi, James M. Brown, Andrew Beers, Bruce R. Rosen, Daniel L. Rubin, Jayashree Kalpathy-Cramer
2018	J	`jnl`	Expanding a radiology lexicon using contextual patterns in radiology reports. J. Am. Medical Informatics Assoc. Bethany Percha, Yuhao Zhang, Selen Bozkurt, Daniel L. Rubin, Russ B. Altman, Curtis P. Langlotz
2018	J	`jnl`	Probabilistic Prognostic Estimates of Survival in Metastatic Cancer Patients (PPES-Met) Utilizing Free-Text Clinical Narratives. CoRR Imon Banerjee, Michael Francis Gensheimer, Douglas J. Wood, Solomon Henry, Daniel T. Chang, Daniel L. Rubin
2018	J	`jnl`	Proposing New RadLex Terms by Analyzing Free-Text Mammography Reports. J. Digit. Imaging Hakan Bulu, Dorothy A. Sippo, Janie M. Lee, Elizabeth S. Burnside, Daniel L. Rubin
2018	J	`jnl`	Quantitative Image Feature Engine (QIFE): an Open-Source, Modular Engine for 3D Quantitative Feature Extraction from Volumetric Medical Images. J. Digit. Imaging Sebastian Echegaray, Shaimaa Bakr, Daniel L. Rubin, Sandy Napel
2018	J	`jnl`	Radiology report annotation using intelligent word embeddings: Applied to multi-institutional chest CT cohort. J. Biomed. Informatics Imon Banerjee, Matthew C. Chen, Matthew P. Lungren, Daniel L. Rubin
2018	J	`jnl`	Relevance feedback for enhancing content based image retrieval and automatic prediction of semantic image features: Application to bone tumor radiographs. J. Biomed. Informatics Imon Banerjee, Camille Kurtz, Alon Edward Devorah, Bao H. Do, Daniel L. Rubin, Christopher F. Beaulieu
2018	J	`jnl`	The LOINC RSNA radiology playbook - a unified terminology for radiology procedures. J. Am. Medical Informatics Assoc. Daniel J. Vreeman, Swapna Abhyankar, Kenneth C. Wang, Chris Carr, Beverly Collins, Daniel L. Rubin, Curtis P. Langlotz
2018	J	`jnl`	Transfer learning on fused multiparametric MR images for classifying histopathological subtypes of rhabdomyosarcoma. Comput. Medical Imaging Graph. Imon Banerjee, Alexis Crawley, Mythili Bhethanabotla, Heike E. Daldrup-Link, Daniel L. Rubin
2018	Misc	`conf`	Unraveling the Molecular Basis of Lung Adenocarcinoma Dedifferentiation and Prognosis by Integrating Omics and Histopathology. AMIA Kun-Hsing Yu, Gerald J. Berry, Daniel L. Rubin, Christopher Ré, Russ B. Altman, Michael Snyder
2017	J	`jnl`	A Convolutional Neural Network for Automatic Characterization of Plaque Composition in Carotid Ultrasound. IEEE J. Biomed. Health Informatics Karim Lekadir, Alfiia Galimzianova, Àngels Betriu, Maria del Mar Vila, Laura Igual, Daniel L. Rubin, Elvira Fernández, Petia Radeva, Sandy Napel
2017	J	`jnl`	A Fully-Automated Pipeline for Detection and Segmentation of Liver Lesions and Pathological Lymph Nodes. CoRR Assaf Hoogi, John W. Lambert, Yefeng Zheng, Dorin Comaniciu, Daniel L. Rubin
2017	J	`jnl`	Adaptive Estimation of Active Contour Parameters Using Convolutional Neural Networks and Texture Analysis. IEEE Trans. Medical Imaging Assaf Hoogi, Arjun Subramaniam, Rishi Veerapaneni, Daniel L. Rubin
2017	J	`jnl`	Adaptive local window for level set segmentation of CT and MRI liver lesions. Medical Image Anal. Assaf Hoogi, Christopher F. Beaulieu, Guilherme M. Cunha, Elhamy Heba, Claude B. Sirlin, Sandy Napel, Daniel L. Rubin
2017	J	`jnl`	Building and Querying RDF/OWL Database of Semantically Annotated Nuclear Medicine Images. J. Digit. Imaging Kyung Hoon Hwang, Haejun Lee, Geon Koh, Debra Willrett, Daniel L. Rubin
2017	J	`jnl`	Computerized Prediction of Radiological Observations Based on Quantitative Feature Analysis: Initial Experience in Liver Lesions. J. Digit. Imaging Imon Banerjee, Christopher F. Beaulieu, Daniel L. Rubin
2017	J	`jnl`	Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions. J. Digit. Imaging Zeynettin Akkus, Alfiia Galimzianova, Assaf Hoogi, Daniel L. Rubin, Bradley J. Erickson
2017	Misc	`conf`	Differential Data Augmentation Techniques for Medical Imaging Classification Tasks. AMIA Zeshan Hussain, Francisco Gimenez, Darvin Yi, Daniel L. Rubin
2017	J	`jnl`	Dynamic strategy for personalized medicine: An application to metastatic breast cancer. J. Biomed. Informatics Xi Chen, Ross D. Shachter, Allison W. Kurian, Daniel L. Rubin
2017	—	`conf`	Inferring Generative Model Structure with Static Analysis. NIPS Paroma Varma, Bryan D. He, Payal Bajaj, Nishith Khandwala, Imon Banerjee, Daniel L. Rubin, Christopher Ré
2017	J	`jnl`	Inferring Generative Model Structure with Static Analysis. CoRR Paroma Varma, Bryan D. He, Payal Bajaj, Imon Banerjee, Nishith Khandwala, Daniel L. Rubin, Christopher Ré
2017	J	`jnl`	Institutionally Distributed Deep Learning Networks. CoRR Ken Chang, Niranjan Balachandar, Carson K. Lam, Darvin Yi, James M. Brown, Andrew Beers, Bruce R. Rosen, Daniel L. Rubin, Jayashree Kalpathy-Cramer
2017	Misc	`conf`	Intelligent Word Embeddings of Free-Text Radiology Reports. AMIA Imon Banerjee, Sriraman Madhavan, Roger Eric Goldman, Daniel L. Rubin
2017	J	`jnl`	Intelligent Word Embeddings of Free-Text Radiology Reports. CoRR Imon Banerjee, Sriraman Madhavan, Roger Eric Goldman, Daniel L. Rubin
2017	J	`jnl`	Optimizing and Visualizing Deep Learning for Benign/Malignant Classification in Breast Tumors. CoRR Darvin Yi, Rebecca Lynn Sawyer, David Cohn III, Jared Dunnmon, Carson K. Lam, Xuerong Xiao, Daniel L. Rubin
2017	J	`jnl`	Piecewise convexity of artificial neural networks. Neural Networks Blaine Rister, Daniel L. Rubin
2017	Misc	`conf`	Predicting Non-Small Cell Lung Cancer Diagnosis and Prognosis by Fully Automated Microscopic Pathology Image Features. AMIA Kun-Hsing Yu, Ce Zhang, Gerald J. Berry, Russ B. Altman, Christopher Ré, Daniel L. Rubin, Michael Snyder
2017	J	`jnl`	Robust noise region-based active contour model via local similarity factor for image segmentation. Pattern Recognit. Sijie Niu, Qiang Chen, Luis de Sisternes, Zexuan Ji, Ze Ming Zhou, Daniel L. Rubin
2017	—	`conf`	Standardized communications of quantitative image analysis results using DICOM: Establishing interoperability through outreach and community engagement. CRI Andriy Fedorov, Daniel L. Rubin, David A. Clunie, Steve Pieper, Ron Kikinis
2017	Misc	`conf`	The LOINC/RSNA Radiology Playbook: A unified terminology for radiology procedures. AMIA Daniel J. Vreeman, Ken Wang, Chris Carr, Beverly Collins, Swapna Abhyankar, Jamalynne Deckard, Clement J. McDonald, Daniel L. Rubin, Curtis P. Langlotz
2017	Misc	`conf`	Toward Automated Pre-Biopsy Thyroid Cancer Risk Estimation in Ultrasound. AMIA Alfiia Galimzianova, Sean M. Siebert, Aya Kamaya, Terry S. Desser, Daniel L. Rubin
2017	J	`jnl`	Volumetric Image Registration From Invariant Keypoints. IEEE Trans. Image Process. Blaine Rister, Mark A. Horowitz, Daniel L. Rubin
2016	J	`jnl`	A 3-D Riesz-Covariance Texture Model for Prediction of Nodule Recurrence in Lung CT. IEEE Trans. Medical Imaging Pol Cirujeda, Yashin Dicente Cid, Henning Müller, Daniel L. Rubin, Todd A. Aguilera, Billy W. Loo, Maximilian Diehn, Xavier Binefa, Adrien Depeursinge
2016	J	`jnl`	Adaptive Local Window for Level Set Segmentation of CT and MRI Liver Lesions. CoRR Assaf Hoogi, Christopher F. Beaulieu, Guilherme M. Cunha, Elhamy Heba, Claude B. Sirlin, Sandy Napel, Daniel L. Rubin
2016	J	`jnl`	Automated classification of brain tumor type in whole-slide digital pathology images using local representative tiles. Medical Image Anal. Jocelyn Barker, Assaf Hoogi, Adrien Depeursinge, Daniel L. Rubin
2016	J	`jnl`	Computerized Multiparametric MR image Analysis for Prostate Cancer Aggressiveness-Assessment. CoRR Imon Banerjee, Lewis Hahn, Geoffrey A. Sonn, Richard E. Fan, Daniel L. Rubin
2016	J	`jnl`	Improved Patch-Based Automated Liver Lesion Classification by Separate Analysis of the Interior and Boundary Regions. IEEE J. Biomed. Health Informatics Idit Diamant, Assaf Hoogi, Christopher F. Beaulieu, Mustafa Safdari, Eyal Klang, Michal Amitai, Hayit Greenspan, Daniel L. Rubin
2016	J	`jnl`	Toward rapid learning in cancer treatment selection: An analytical engine for practice-based clinical data. J. Biomed. Informatics Samuel G. Finlayson, Mia A. Levy, Sunil Reddy, Daniel L. Rubin
2016	J	`jnl`	Using automatically extracted information from mammography reports for decision-support. J. Biomed. Informatics Selen Bozkurt, Francisco Gimenez, Elizabeth S. Burnside, Kemal Hakan Gülkesen, Daniel L. Rubin
2015	B	`conf`	3D Markup of Radiological Images in ePAD, a Web-Based Image Annotation Tool. CBMS Dilvan A. Moreira, Cleber Hage, Edson F. Luque, Debra Willrett, Daniel L. Rubin
2015	—	`conf`	3D Riesz-wavelet based Covariance descriptors for texture classification of lung nodule tissue in CT. EMBC Pol Cirujeda, Henning Müller, Daniel L. Rubin, Todd A. Aguilera, Billy W. Loo, Maximilian Diehn, Xavier Binefa, Adrien Depeursinge
2015	J	`jnl`	Application of Improved Homogeneity Similarity-Based Denoising in Optical Coherence Tomography Retinal Images. J. Digit. Imaging Qiang Chen, Luis de Sisternes, Theodore Leng, Daniel L. Rubin
2015	Misc	`conf`	Automated Grading of Gliomas using Deep Learning in Digital Pathology Images: A modular approach with ensemble of convolutional neural networks. AMIA Mehmet Günhan Ertosun, Daniel L. Rubin
2015	B	`conf`	Automatic Classification of Cancer Tumors Using Image Annotations and Ontologies. CBMS Edson F. Luque, Daniel L. Rubin, Dilvan A. Moreira
2015	J	`jnl`	Automatic abstraction of imaging observations with their characteristics from mammography reports. J. Am. Medical Informatics Assoc. Selen Bozkurt, Jafi A. Lipson, Utku Senol, Daniel L. Rubin
2015	J	`jnl`	Comparing image search behaviour in the ARRS GoldMiner search engine and a clinical PACS/RIS. J. Biomed. Informatics Maria De-Arteaga, Ivan Eggel, Bao H. Do, Daniel L. Rubin, Charles E. Kahn Jr., Henning Müller
2015	—	`conf`	Optimized steerable wavelets for texture analysis of lung tissue in 3-D CT: Classification of usual interstitial pneumonia. ISBI Adrien Depeursinge, Pedram Pad, Anne S. Chin, Ann N. Leung, Daniel L. Rubin, Henning Müller, Michael Unser
2015	Misc	`conf`	Polychromatic X-Ray Absorptiometry to Quantify Breast Density Volume, Ratio and their Associated Breast Cancer Risk in Full-Digital Mammography. AMIA Luis de Sisternes, Joseph Rothstein, Abra Jeffers, Weiva Sieh, Daniel L. Rubin
2015	—	`conf`	Probabilistic visual search for masses within mammography images using deep learning. BIBM Mehmet Günhan Ertosun, Daniel L. Rubin
2015	—	`conf`	Semantic Retrieval of Radiological Images with Relevance Feedback. MRDM@ECIR Camille Kurtz, Paul-André Idoux, Avinash Thangali, Florence Cloppet, Christopher F. Beaulieu, Daniel L. Rubin
2015	—	`conf`	Weighted locality-constrained linear coding for lesion classification in CT images. EMBC Yixuan Yuan, Assaf Hoogi, Christopher F. Beaulieu, Max Q.-H. Meng, Daniel L. Rubin
2015	Misc	`conf`	ePAD: Leveraging image data in learning healthcare systems. AMIA Daniel L. Rubin
2014	Misc	`conf`	A Novel Method to Assess Incompleteness of Mammography Report Content. AMIA Francisco Gimenez, Yirong Wu, Elizabeth S. Burnside, Daniel L. Rubin
2014	J	`jnl`	A hierarchical knowledge-based approach for retrieving similar medical images described with semantic annotations. J. Biomed. Informatics Camille Kurtz, Christopher F. Beaulieu, Sandy Napel, Daniel L. Rubin
2014	B	`conf`	A semantic framework for the retrieval of similar radiological images based on medical annotations. ICIP Camille Kurtz, Adrien Depeursinge, Christopher F. Beaulieu, Daniel L. Rubin
2014	J	`jnl`	Automated retinal layers segmentation in SD-OCT images using dual-gradient and spatial correlation smoothness constraint. Comput. Biol. Medicine Sijie Niu, Qiang Chen, Luis de Sisternes, Daniel L. Rubin, Weiwei Zhang, Qinghuai Liu
2014	J	`jnl`	Classification of hepatic lesions using the matching metric. Comput. Vis. Image Underst. Aaron Adcock, Daniel L. Rubin, Gunnar E. Carlsson
2014	—	`conf`	Extracting Imaging Observation Entities in Mammography Reports. MIE Selen Bozkurt, Daniel L. Rubin
2014	J	`jnl`	Neuroanatomical domain of the foundational model of anatomy ontology. J. Biomed. Semant. B. Nolan Nichols, José L. V. Mejino Jr., Landon Detwiler, Trond T. Nilsen, Maryann E. Martone, Jessica A. Turner, Daniel L. Rubin, James F. Brinkley
2014	J	`jnl`	On combining image-based and ontological semantic dissimilarities for medical image retrieval applications. Medical Image Anal. Camille Kurtz, Adrien Depeursinge, Sandy Napel, Christopher F. Beaulieu, Daniel L. Rubin
2014	J	`jnl`	Predicting Visual Semantic Descriptive Terms From Radiological Image Data: Preliminary Results With Liver Lesions in CT. IEEE Trans. Medical Imaging Adrien Depeursinge, Camille Kurtz, Christopher F. Beaulieu, Sandy Napel, Daniel L. Rubin
2014	J	`jnl`	Software for Distributed Computation on Medical Databases: A Demonstration Project. CoRR Balasubramanian Narasimhan, Daniel L. Rubin, Samuel M. Gross, Marina Bendersky, Philip W. Lavori
2014	J	`jnl`	The National Cancer Informatics Program (NCIP) Annotation and Image Markup (AIM) Foundation Model. J. Digit. Imaging Pattanasak Mongkolwat, Vladimir Kleper, Skip Talbot, Daniel L. Rubin
2014	—	`conf`	Utilisation de relations ontologiques pour la comparaison d'images décrites par des annotations sémantiques. EGC Camille Kurtz, Daniel L. Rubin
2013	J	`jnl`	ACR-AAPM-SIIM Practice Guideline for Determinants of Image Quality in Digital Mammography. J. Digit. Imaging Kalpana M. Kanal, Elizabeth A. Krupinski, Eric A. Berns, William R. Geiser, Andrew Karellas, Martha B. Mainiero, Melissa C. Martin, Samir B. Patel, Daniel L. Rubin, Jon D. Shepard, Eliot L. Siegel, Judith A. Wolfman, Tariq A. Mian, Mary C. Mahoney, Margaret Wyatt
2013	—	`conf`	Annotation for Information Extraction from Mammography Reports. ICIMTH Selen Bozkurt, Kemal Hakan Gülkesen, Daniel L. Rubin
2013	J	`jnl`	Automated drusen segmentation and quantification in SD-OCT images. Medical Image Anal. Qiang Chen, Theodore Leng, Luoluo Zheng, Lauren Kutzscher, Jeffrey J. Ma, Luis de Sisternes, Daniel L. Rubin
2013	Misc	`conf`	Classifying Benign and Malignant Lung Diseases by Applying Machine Learning Methods to Microscopic Pathology Images. AMIA Kun-Hsing Yu, Shanshan Tuo, Daniel L. Rubin
2013	J	`jnl`	Erratum to: Quantitative Imaging Biomarker Ontology (QIBO) for Knowledge Representation of Biomedical Imaging Biomarkers. J. Digit. Imaging Andrew J. Buckler, Tiffany Ting Liu, Erica S. Savig, Baris E. Suzek, Daniel L. Rubin, David Paik
2013	—	`conf`	Image patch-based method for automated classification and detection of focal liver lesions on CT. Computer-Aided Diagnosis Mustafa Safdari, Raghav Pasari, Daniel L. Rubin, Hayit Greenspan
2013	J	`jnl`	Modeling Perceptual Similarity Measures in CT Images of Focal Liver Lesions. J. Digit. Imaging Jessica S. Faruque, Daniel L. Rubin, Christopher F. Beaulieu, Sandy Napel
2013	J	`jnl`	Quantitative Imaging Biomarker Ontology (QIBO) for Knowledge Representation of Biomedical Imaging Biomarkers. J. Digit. Imaging Andrew J. Buckler, Matt Ouellette, Jovanna Danagoulian, Gary Wernsing, Tiffany Ting Liu, Erica S. Savig, Baris E. Suzek, Daniel L. Rubin, David Paik
2013	J	`jnl`	Research and applications: Dynamic contrast-enhanced MRI-based biomarkers of therapeutic response in triple-negative breast cancer. J. Am. Medical Informatics Assoc. Daniel I. Golden, Jafi A. Lipson, Melinda L. Telli, James M. Ford, Daniel L. Rubin
2013	J	`jnl`	Snake model-based lymphoma segmentation for sequential CT images. Comput. Methods Programs Biomed. Qiang Chen, Fang Quan, Jiajing Xu, Daniel L. Rubin
2012	J	`jnl`	A Comprehensive Descriptor of Shape: Method and Application to Content-Based Retrieval of Similar Appearing Lesions in Medical Images. J. Digit. Imaging Jiajing Xu, Jessica S. Faruque, Christopher F. Beaulieu, Daniel L. Rubin, Sandy Napel
2012	J	`jnl`	A Hybrid Method for Distance Metric Learning. CoRR Yi-Hao Kao, Benjamin Van Roy, Daniel L. Rubin, Jiajing Xu, Jessica S. Faruque, Sandy Napel
2012	Misc	`conf`	Automatic Annotation of Radiological Observations in Liver CT Images. AMIA Francisco Gimenez, Jiajing Xu, Yi Liu, Tiffany Ting Liu, Christopher F. Beaulieu, Daniel L. Rubin, Sandy Napel
2012	J	`jnl`	Automatic classification of mammography reports by BI-RADS breast tissue composition class. J. Am. Medical Informatics Assoc. Bethany Percha, Houssam Nassif, Jafi A. Lipson, Elizabeth S. Burnside, Daniel L. Rubin
2012	J	`jnl`	Classification of Hepatic Lesions using the Matching Metric CoRR Aaron Adcock, Daniel L. Rubin, Gunnar E. Carlsson
2012	J	`jnl`	Integration of Imaging Signs into RadLex. J. Digit. Imaging Matthew W. Shore, Daniel L. Rubin, Charles E. Kahn Jr.
2012	C	`conf`	Using the Semantic Web and Web Apps to Connect Radiologists and Oncologists. WETICE Kleberson J. A. Serique, Alan Snyder, Debra Willrett, Daniel L. Rubin, Dilvan A. Moreira
2011	—	`conf`	A Scalable Reference Standard of Visual Similarity for a Content-Based Image Retrieval System. HISB Jessica S. Faruque, Daniel L. Rubin, Christopher F. Beaulieu, Jarrett Rosenberg, Aya Kamaya, Grace Tye, Sandy Napel, Ronald M. Summers
2011	J	`jnl`	A practical method for transforming free-text eligibility criteria into computable criteria. J. Biomed. Informatics Samson W. Tu, Mor Peleg, Simona Carini, Michael Bobak, Jessica Ross, Daniel L. Rubin, Ida Sim
2011	J	`jnl`	Content-Based Image Retrieval in Radiology: Current Status and Future Directions. J. Digit. Imaging Ceyhun Burak Akgül, Daniel L. Rubin, Sandy Napel, Christopher F. Beaulieu, Hayit Greenspan, Burak Acar
2011	J	`jnl`	Evaluation of Negation and Uncertainty Detection and its Impact on Precision and Recall in Search. J. Digit. Imaging Andrew S. Wu, Bao H. Do, Jinsuh Kim, Daniel L. Rubin
2011	J	`jnl`	Managing Biomedical Image Metadata for Search and Retrieval of Similar Images. J. Digit. Imaging Daniel Korenblum, Daniel L. Rubin, Sandy Napel, Cesar Rodriguez, Christopher F. Beaulieu
2011	—	`conf`	On the Feasibility of Predicting Radiological Observations from Computational Imaging Features of Liver Lesions in CT Scans. HISB Francisco Gimenez, Jiajing Xu, Yi Liu, Tiffany Ting Liu, Christopher F. Beaulieu, Daniel L. Rubin, Sandy Napel
2011	J	`jnl`	Ontology-Assisted Analysis of Web Queries to Determine the Knowledge Radiologists Seek. J. Digit. Imaging Daniel L. Rubin, Adam E. Flanders, Woojin Kim, Khan M. Siddiqui, Charles E. Kahn
2011	J	`jnl`	The Biomedical Resource Ontology (BRO) to enable resource discovery in clinical and translational research. J. Biomed. Informatics Jessica D. Tenenbaum, Patricia L. Whetzel, Kent Anderson, Charles D. Borromeo, Ivo D. Dinov, Davera Gabriel, Beth A. Kirschner, Barbara Mirel, Timothy D. Morris, Natasha Fridman Noy, Csongor Nyulas, David Rubenson, Paul R. Saxman, Harpreet Singh, Nancy Whelan, Zach Wright, Brian D. Athey, Michael J. Becich, Geoffrey S. Ginsburg, Mark A. Musen, Kevin A. Smith, Alice F. Tarantal, Daniel L. Rubin, Peter Lyster
2010	J	`jnl`	An Integrative Approach for In Silico Glioma Research. IEEE Trans. Biomed. Eng. Lee A. D. Cooper, Jun Kong, David A. Gutman, Fusheng Wang, Sharath R. Cholleti, Tony C. Pan, Patrick M. Widener, Ashish Sharma, Tom Mikkelsen, Adam E. Flanders, Daniel L. Rubin, Erwin G. Van Meir, Tahsin M. Kurç, Carlos Sanchez Moreno, Daniel J. Brat, Joel H. Saltz
2010	J	`jnl`	Application of neuroanatomical ontologies for neuroimaging data annotation. Frontiers Neuroinformatics Jessica A. Turner, José L. V. Mejino Jr., James F. Brinkley, Landon T. Detwiler, Hyo Jong Lee, Maryann E. Martone, Daniel L. Rubin
2010	B	`ed.`	IEEE 23rd International Symposium on Computer-Based Medical Systems (CBMS 2010), Perth, Australia, October 12-15, 2010 CBMS Tharam S. Dillon, Daniel L. Rubin, William M. Gallagher, Amandeep S. Sidhu, Alexey Tsymbal
2010	J	`jnl`	The caBIG J. Digit. Imaging David S. Channin, Pattanasak Mongkolwat, Vladimir Kleper, Kastubh Sepukar, Daniel L. Rubin
2009	J	`jnl`	Annotation and Image Markup: Accessing and Interoperating with the Semantic Content in Medical Imaging. IEEE Intell. Syst. Daniel L. Rubin, Pattanasak Mongkolwat, Vladimir Kleper, Kaustubh Supekar, David S. Channin
2009	J	`jnl`	BioPortal: ontologies and integrated data resources at the click of a mouse. Nucleic Acids Res. Natalya Fridman Noy, Nigam H. Shah, Patricia L. Whetzel, Benjamin Dai, Michael Dorf, Nicholas Griffith, Clément Jonquet, Daniel L. Rubin, Margaret-Anne D. Storey, Christopher G. Chute, Mark A. Musen
2009	J	`jnl`	Comparison of concept recognizers for building the Open Biomedical Annotator. BMC Bioinform. Nigam H. Shah, Nipun Bhatia, Clément Jonquet, Daniel L. Rubin, Annie P. Chiang, Mark A. Musen
2009	J	`jnl`	Computational neuroanatomy: ontology-based representation of neural components and connectivity. BMC Bioinform. Daniel L. Rubin, Ion-Florin Talos, Michael Halle, Mark A. Musen, Ron Kikinis
2009	J	`jnl`	Research Paper: Automated Semantic Indexing of Figure Captions to Improve Radiology Image Retrieval. J. Am. Medical Informatics Assoc. Charles E. Kahn Jr., Daniel L. Rubin
2009	Misc	`conf`	Semantic Reasoning with Image Annotations for Tumor Assessment. AMIA Mia A. Levy, Martin J. O'Connor, Daniel L. Rubin
2008	Misc	`conf`	A Bayesian Classifier for Differentiating Benign versus Malignant Thyroid Nodules using Sonographic Features. AMIA Yueyi I. Liu, Aya Kamaya, Terry S. Desser, Daniel L. Rubin
2008	J	`jnl`	A prototype symbolic model of canonical functional neuroanatomy of the motor system. J. Biomed. Informatics Ion-Florin Talos, Daniel L. Rubin, Michael Halle, Mark A. Musen, Ron Kikinis
2008	—	`conf`	BioPortal: A Web Portal to Biomedical Ontologies. AAAI Spring Symposium: Symbiotic Relationships between Semantic Web and Knowledge Engineering Daniel L. Rubin, Dilvan A. Moreira, Pradip Kanjamala, Mark A. Musen
2008	—	`conf`	BioPortal: A Web Repository for Biomedical Ontologies and Data Resources. ISWC (Posters & Demos) Natalya Fridman Noy, Nigam Shah, Benjamin Dai, Michael Dorf, Nicholas Griffith, Clément Jonquet, Michael Montegut, Daniel L. Rubin, Cherie Youn, Mark A. Musen
2008	J	`jnl`	Biomedical ontologies: a functional perspective. Briefings Bioinform. Daniel L. Rubin, Nigam Shah, Natalya Fridman Noy
2008	J	`jnl`	Creating and Curating a Terminology for Radiology: Ontology Modeling and Analysis. J. Digit. Imaging Daniel L. Rubin
2008	Misc	`conf`	FMA-RadLex: An Application Ontology of Radiological Anatomy derived from the Foundational Model of Anatomy Reference Ontology. AMIA José L. V. Mejino Jr., Daniel L. Rubin, James F. Brinkley
2008	J	`jnl`	MScanner: a classifier for retrieving Medline citations. BMC Bioinform. Graham L. Poulter, Daniel L. Rubin, Russ B. Altman, Cathal Seoighe
2008	—	`conf`	Medical Imaging on the Semantic Web: Annotation and Image Markup. AAAI Spring Symposium: Semantic Scientific Knowledge Integration Daniel L. Rubin, Pattanasak Mongkolwat, Vladimir Kleper, Kaustubh Supekar, David S. Channin
2008	J	`jnl`	Network Analysis of Intrinsic Functional Brain Connectivity in Alzheimer's Disease. PLoS Comput. Biol. Kaustubh Supekar, Vinod Menon, Daniel L. Rubin, Mark A. Musen, Michael D. Greicius
2008	J	`jnl`	The NIFSTD and BIRNLex Vocabularies: Building Comprehensive Ontologies for Neuroscience. Neuroinformatics William J. Bug, Giorgio A. Ascoli, Jeffrey S. Grethe, Amarnath Gupta, Christine Fennema-Notestine, Angela R. Laird, Stephen D. Larson, Daniel L. Rubin, Gordon M. Shepherd, Jessica A. Turner, Maryann E. Martone
2008	Misc	`conf`	Tool Support to Enable Evaluation of the Clinical Response to Treatment. AMIA Mia A. Levy, Daniel L. Rubin
2008	J	`jnl`	Translating the Foundational Model of Anatomy into OWL. J. Web Semant. Natalya Fridman Noy, Daniel L. Rubin
2007	J	`jnl`	Annotation and query of tissue microarray data using the NCI Thesaurus. BMC Bioinform. Nigam H. Shah, Daniel L. Rubin, Inigo Espinosa, Kelli Montgomery, Mark A. Musen
2007	—	`conf`	Knowledge Zone: A Public Repository of Peer-Reviewed Biomedical Ontologies. MedInfo Kaustubh Supekar, Daniel L. Rubin, Natasha F. Noy, Mark A. Musen
2007	Misc	`conf`	LesionViewer: A Tool for Tracking Cancer Lesions Over Time. AMIA Mia A. Levy, Ankit Garg, Aaron Tam, Yael Garten, Daniel L. Rubin
2007	—	`conf`	Using Annotations from Controlled Vocabularies to Find Meaningful Associations. DILS Woei-Jyh Lee, Louiqa Raschid, Padmini Srinivasan, Nigam Shah, Daniel L. Rubin, Natasha Fridman Noy
2006	J	`jnl`	An Ontology for PACS Integration. J. Digit. Imaging Charles E. Kahn, David S. Channin, Daniel L. Rubin
2006	Misc	`conf`	Ontology-Based Representation of Simulation Models of Physiology. AMIA Daniel L. Rubin, David Grossman, Maxwell Lewis Neal, Daniel L. Cook, James B. Bassingthwaighte, Mark A. Musen
2006	Misc	`conf`	Ontology-based Annotation and Query of Tissue Microarray Data. AMIA Nigam H. Shah, Daniel L. Rubin, Kaustubh S. Supekar, Mark A. Musen
2006	J	`jnl`	Using ontologies linked with geometric models to reason about penetrating injuries. Artif. Intell. Medicine Daniel L. Rubin, Olivier Dameron, Yasser Bashir, David Grossman, Parvati Dev, Mark A. Musen
2005	J	`jnl`	Application of Information Technology: A Statistical Approach to Scanning the Biomedical Literature for Pharmacogenetics Knowledge. J. Am. Medical Informatics Assoc. Daniel L. Rubin, Caroline F. Thorn, Teri E. Klein, Russ B. Altman
2005	Misc	`conf`	Challenges in Converting Frame-Based Ontology into OWL: the Foundational Model of Anatomy Case-Study. AMIA Olivier Dameron, Daniel L. Rubin, Mark A. Musen
2005	Misc	`conf`	Protégé-OWL: Creating Ontology-Driven Reasoning Applications with the Web Ontology Language. AMIA Daniel L. Rubin, Holger Knublauch, Ray W. Fergerson, Olivier Dameron, Mark A. Musen
2005	J	`jnl`	Research Paper: Using Petri Net Tools to Study Properties and Dynamics of Biological Systems. J. Am. Medical Informatics Assoc. Mor Peleg, Daniel L. Rubin, Russ B. Altman
2005	Misc	`conf`	Use of Description Logic Classification to Reason about Consequences of Penetrating Injuries. AMIA Daniel L. Rubin, Olivier Dameron, Mark A. Musen
2004	—	`conf`	A Resource to Acquire and Summarize Pharmacogenetics Knowledge in the Literature. MedInfo Daniel L. Rubin, Michelle Whirl Carrillo, Mark Woon, John Conroy, Teri E. Klein, Russ B. Altman
2004	—	`conf`	Improving a Bayesian network's ability to predict the probability of malignancy of microcalcifications on mammography. CARS Elizabeth S. Burnside, Daniel L. Rubin, Ross D. Shachter
2004	J	`jnl`	Making Biomedical Ontologies and Ontology Repositories Work. IEEE Intell. Syst. Natalya Fridman Noy, Daniel L. Rubin, Mark A. Musen
2004	—	`conf`	Using a Bayesian Network to Predict the Probability and Type of Breast Cancer Represented by Microcalcifications on Mammography. MedInfo Elizabeth S. Burnside, Daniel L. Rubin, Ross D. Shachter
2002	Misc	`conf`	Automating Data Acquisition into Ontologies from Pharmacogenetics Relational Data Sources Using Declarative Object Definitions and XML. Pacific Symposium on Biocomputing Daniel L. Rubin, Micheal Hewett, Diane E. Oliver, Teri E. Klein, Russ B. Altman
2002	Misc	`conf`	Ontology Development for a Pharmacogenetics Knowledge Base. Pacific Symposium on Biocomputing Diane E. Oliver, Daniel L. Rubin, Joshua M. Stuart, Micheal Hewett, Teri E. Klein, Russ B. Altman
2002	J	`jnl`	PharmGKB: the Pharmacogenetics Knowledge Base. Nucleic Acids Res. Micheal Hewett, Diane E. Oliver, Daniel L. Rubin, Katrina L. Easton, Joshua M. Stuart, Russ B. Altman, Teri E. Klein
2002	A	`conf`	Representing genetic sequence data for pharmacogenomics: an evolutionary approach using ontological and relational models. ISMB Daniel L. Rubin, Farhad Shafa, Diane E. Oliver, Micheal Hewett, Russ B. Altman
2000	Misc	`conf`	A Bayesian network for mammography. AMIA Elizabeth S. Burnside, Daniel L. Rubin, Ross D. Shachter
2000	Misc	`conf`	Knowledge representation and tool support for critiquing clinical trial protocols. AMIA Daniel L. Rubin, John H. Gennari, Mark A. Musen
1999	Misc	`conf`	Tool support for authoring eligibility criteria for cancer trials. AMIA Daniel L. Rubin, John H. Gennari, Sandra Srinivas, Allen Yuen, Herbert Kaizer, Mark A. Musen, John S. Silva