Narges Razavian

43 papers A* 4Misc 2Journal 29Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Cerebra: A Multidisciplinary AI Board for Multimodal Dementia Characterization and Risk Assessment. CoRR Sheng Liu, Long Chen, Zeyun Zhao, Qinglin Gou, Qingyue Wei, Arjun Masurkar, Kevin M. Spiegler, Philip Kuball, Stefania C. Bray, Megan Bernath, Deanna R. Willis, Jiang Bian, Lei Xing, Eric Topol, Kyunghyun Cho, Yu Huang, Ruogu Fang, Narges Razavian, James Zou
2026	J	`jnl`	Scaling Recurrence-aware Foundation Models for Clinical Records via Next-Visit Prediction. CoRR Haresh Rengaraj Rajamohan, Xiang Gao, Weicheng Zhu, Shih-Lun Huang, Long Chen, Gabe Schulman, Huizhen Jin, Shengduo Li, Yixuan Wang, Huidi Yang, Kyunghyun Cho, Cem M. Deniz, Narges Razavian
2025	J	`jnl`	3D Foundation AI Model for Generalizable Disease Detection in Head Computed Tomography. CoRR Weicheng Zhu, Haoxu Huang, Huanze Tang, Rushabh Musthyala, Boyang Yu, Long Chen, Emilio Vega, Thomas O'Donnell, Seena Dehkharghani, Jennifer A. Frontera, Arjun V. Masurkar, Kara Melmed, Narges Razavian
2025	J	`jnl`	Foundation Models for Clinical Records at Health System Scale. CoRR Haresh Rengaraj Rajamohan, Xiang Gao, Weicheng Zhu, Shih-Lun Huang, Long Chen, Kyunghyun Cho, Cem M. Deniz, Narges Razavian
2025	J	`jnl`	Making Self-supervised Learning Robust to Spurious Correlation via Learning-speed Aware Sampling. Trans. Mach. Learn. Res. Weicheng Zhu, Sheng Liu, Carlos Fernandez-Granda, Narges Razavian
2023	J	`jnl`	Automatic Detection of Alzheimer's Disease with Multi-Modal Fusion of Clinical MRI Scans. CoRR Long Chen, Liben Chen, Binfeng Xu, Wenxin Zhang, Narges Razavian
2023	J	`jnl`	Making Self-supervised Learning Robust to Spurious Correlation via Learning-speed Aware Sampling. CoRR Weicheng Zhu, Sheng Liu, Carlos Fernandez-Granda, Narges Razavian
2023	A*	`conf`	Multiple Instance Learning via Iterative Self-Paced Supervised Contrastive Learning. CVPR Kangning Liu, Weicheng Zhu, Yiqiu Shen, Sheng Liu, Narges Razavian, Krzysztof J. Geras, Carlos Fernandez-Granda
2022	A*	`conf`	Deep Probability Estimation. ICML Sheng Liu, Aakash Kaku, Weicheng Zhu, Matan Leibovich, Sreyas Mohan, Boyang Yu, Haoxiang Huang, Laure Zanna, Narges Razavian, Jonathan Niles-Weed, Carlos Fernandez-Granda
2022	J	`jnl`	Evaluating the Effect of a COVID-19 Predictive Model to Facilitate Discharge: A Randomized Controlled Trial. Appl. Clin. Inform. Vincent J. Major, Simon Andrew Jones, Narges Razavian, Ashley Bagheri, Felicia Mendoza, Jay Stadelman, Leora I. Horwitz, Jonathan S. Austrian, Yindalon Aphinyanaphongs
2022	—	`conf`	Interpretable Prediction of Lung Squamous Cell Carcinoma Recurrence With Self-supervised Learning. MIDL Weicheng Zhu, Carlos Fernandez-Granda, Narges Razavian
2022	J	`jnl`	Interpretable Prediction of Lung Squamous Cell Carcinoma Recurrence With Self-supervised Learning. CoRR Weicheng Zhu, Carlos Fernandez-Granda, Narges Razavian
2022	J	`jnl`	Multiple Instance Learning via Iterative Self-Paced Supervised Contrastive Learning. CoRR Kangning Liu, Weicheng Zhu, Yiqiu Shen, Sheng Liu, Narges Razavian, Krzysztof J. Geras, Carlos Fernandez-Granda
2021	J	`jnl`	An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department. npj Digit. Medicine Farah E. Shamout, Yiqiu Shen, Nan Wu, Aakash Kaku, Jungkyu Park, Taro Makino, Stanislaw Jastrzebski, Jan Witowski, Duo Wang, Ben Zhang, Siddhant Dogra, Meng Cao, Narges Razavian, David Kudlowitz, Lea Azour, William Moore, Yvonne W. Lui, Yindalon Aphinyanaphongs, Carlos Fernandez-Granda, Krzysztof J. Geras
2021	J	`jnl`	Causal Effect Variational Autoencoder with Uniform Treatment. CoRR Daniel Jiwoong Im, Kyunghyun Cho, Narges Razavian
2021	J	`jnl`	Deep Probability Estimation. CoRR Sheng Liu, Aakash Kaku, Weicheng Zhu, Matan Leibovich, Sreyas Mohan, Boyang Yu, Laure Zanna, Narges Razavian, Carlos Fernandez-Granda
2021	A*	`conf`	Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning. NeurIPS Aakash Kaku, Sahana Upadhya, Narges Razavian
2021	J	`jnl`	Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning. CoRR Aakash Kaku, Sahana Upadhya, Narges Razavian
2021	—	`conf`	Variationally regularized graph-based representation learning for electronic health records. CHIL Weicheng Zhu, Narges Razavian
2020	J	`jnl`	A validated, real-time prediction model for favorable outcomes in hospitalized COVID-19 patients. npj Digit. Medicine Narges Razavian, Vincent J. Major, Mukund Sudarshan, Jesse Burk-Rafel, Peter Stella, Hardev Randhawa, Seda Bilaloglu, Ji Chen, Vuthy Nguy, Walter Wang, Hao Zhang, Ilan Reinstein, David Kudlowitz, Cameron Zenger, Meng Cao, Ruina Zhang, Siddhant Dogra, Keerthi B. Harish, Brian Bosworth, Fritz Francois, Leora I. Horwitz, Rajesh Ranganath, Jonathan S. Austrian, Yindalon Aphinyanaphongs
2020	J	`jnl`	An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department. CoRR Farah E. Shamout, Yiqiu Shen, Nan Wu, Aakash Kaku, Jungkyu Park, Taro Makino, Stanislaw Jastrzebski, Duo Wang, Ben Zhang, Siddhant Dogra, Meng Cao, Narges Razavian, David Kudlowitz, Lea Azour, William Moore, Yvonne W. Lui, Yindalon Aphinyanaphongs, Carlos Fernandez-Granda, Krzysztof J. Geras
2020	—	`conf`	BERT-XML: Large Scale Automated ICD Coding Using BERT Pretraining. ClinicalNLP@EMNLP Zachariah Zhang, Jingshu Liu, Narges Razavian
2020	J	`jnl`	BERT-XML: Large Scale Automated ICD Coding Using BERT Pretraining. CoRR Zachariah Zhang, Jingshu Liu, Narges Razavian
2020	A*	`conf`	Early-Learning Regularization Prevents Memorization of Noisy Labels. NeurIPS Sheng Liu, Jonathan Niles-Weed, Narges Razavian, Carlos Fernandez-Granda
2020	J	`jnl`	Early-Learning Regularization Prevents Memorization of Noisy Labels. CoRR Sheng Liu, Jonathan Niles-Weed, Narges Razavian, Carlos Fernandez-Granda
2020	—	`conf`	Tracing State-Level Obesity Prevalence from Sentence Embeddings of Tweets: A Feasibility Study. Poly/DMAH@VLDB Xiaoyi Zhang, Rodoniki Athanasiadou, Narges Razavian
2019	J	`jnl`	DARTS: DenseUnet-based Automatic Rapid Tool for brain Segmentation. CoRR Aakash Kaku, Chaitra V. Hegde, Jeffrey Huang, Sohae Chung, Xiuyuan Wang, Matthew Young, Alireza Radmanesh, Yvonne W. Lui, Narges Razavian
2019	J	`jnl`	Graph Neural Network on Electronic Health Records for Predicting Alzheimer's Disease. CoRR Weicheng Zhu, Narges Razavian
2019	—	`conf`	On the design of convolutional neural networks for automatic detection of Alzheimer's disease. ML4H@NeurIPS Sheng Liu, Chhavi Yadav, Carlos Fernandez-Granda, Narges Razavian
2019	J	`jnl`	On the design of convolutional neural networks for automatic detection of Alzheimer's disease. CoRR Sheng Liu, Chhavi Yadav, Carlos Fernandez-Granda, Narges Razavian
2019	J	`jnl`	Towards Quantification of Bias in Machine Learning for Healthcare: A Case Study of Renal Failure Prediction. CoRR Josie Williams, Narges Razavian
2019	J	`jnl`	Tracing State-Level Obesity Prevalence from Sentence Embeddings of Tweets: A Feasibility Study. CoRR Xiaoyi Zhang, Rodoniki Athanasiadou, Narges Razavian
2018	—	`conf`	Deep EHR: Chronic Disease Prediction Using Medical Notes. MLHC Jingshu Liu, Zachariah Zhang, Narges Razavian
2018	J	`jnl`	Deep EHR: Chronic Disease Prediction Using Medical Notes. CoRR Jingshu Liu, Zachariah Zhang, Narges Razavian
2016	J	`jnl`	Multi-task Prediction of Disease Onsets from Longitudinal Lab Tests. CoRR Narges Razavian, Jake Marcus, David A. Sontag
2016	—	`conf`	Multi-task Prediction of Disease Onsets from Longitudinal Laboratory Tests. MLHC Narges Razavian, Jake Marcus, David A. Sontag
2015	J	`jnl`	Advancing the frontier of data-driven healthcare. XRDS Narges Razavian
2015	Misc	`conf`	Gaussian Processes for interpreting Multiple Prostate Specific Antigen measurements for Prostate Cancer Prediction. AMIA Narges Razavian, Saul Blecker, David A. Sontag
2015	J	`jnl`	Population-Level Prediction of Type 2 Diabetes From Claims Data and Analysis of Risk Factors. Big Data Narges Razavian, Saul Blecker, Ann Marie Schmidt, Aaron Smith-McLallen, Somesh Nigam, David A. Sontag
2015	J	`jnl`	Temporal Convolutional Neural Networks for Diagnosis from Lab Tests. CoRR Narges Razavian, David A. Sontag
2015	Misc	`conf`	Visual Exploration of Temporal Data in Electronic Medical Records. AMIA Josua Krause, Narges Razavian, Enrico Bertini, David A. Sontag
2013	—	`—`	Continuous Graphical Models for Static and Dynamic Distributions: Application to Structural Biology. Narges Razavian
2012	J	`jnl`	Learning generative models of molecular dynamics. BMC Genom. Narges Razavian, Hetunandan Kamisetty, Christopher James Langmead