Deepta Rajan - RankMe

37 papers A* 3C 3Misc 1Journal 18Unranked 12

Year	Rank	Type	Title / Venue / Authors
2023	—	`conf`	Exploring Inlier and Outlier Specification for Improved Medical OOD Detection. ICCV (Workshops) Vivek Sivaraman Narayanaswamy, Yamen Mubarka, Rushil Anirudh, Deepta Rajan, Jayaraman J. Thiagarajan
2023	—	`conf`	Know Your Space: Inlier and Outlier Construction for Calibrating Medical OOD Detectors. MIDL Vivek Sivaraman Narayanaswamy, Yamen Mubarka, Rushil Anirudh, Deepta Rajan, Andreas Spanias, Jayaraman J. Thiagarajan
2022	J	`jnl`	Revisiting Inlier and Outlier Specification for Improved Out-of-Distribution Detection. CoRR Vivek Sivaraman Narayanaswamy, Yamen Mubarka, Rushil Anirudh, Deepta Rajan, Andreas Spanias, Jayaraman J. Thiagarajan
2022	J	`jnl`	Self-training of Machine Learning Models for Liver Histopathology: Generalization under Clinical Shifts. CoRR Jin Li, Deepta Rajan, Chintan Shah, Dinkar Juyal, Shreya Chakraborty, Chandan Akiti, Filip Kos, Janani Iyer, Anand Sampat, Ali Behrooz
2021	—	`conf`	Automatic localization of lung opacity in chest CT images: a real-world study. Computer-Aided Diagnosis Yiting Xie, Deepta Rajan, Larissa C. Schudlo, Yusuke Takeuchi, Benedikt Graf, Adam Coy, Mohammadreza Negahdar, Vandana V. Mukherjee, David Beymer, Arun Krishnan
2021	A*	`conf`	Designing Counterfactual Generators using Deep Model Inversion. NeurIPS Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Deepta Rajan, Jason Liang, Akshay Chaudhari, Andreas Spanias
2021	J	`jnl`	Designing Counterfactual Generators using Deep Model Inversion. CoRR Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Deepta Rajan, Jason Liang, Akshay Chaudhari, Andreas Spanias
2021	A*	`conf`	Fair Selective Classification Via Sufficiency. ICML Joshua K. Lee, Yuheng Bu, Deepta Rajan, Prasanna Sattigeri, Rameswar Panda, Subhro Das, Gregory W. Wornell
2021	J	`jnl`	Loss Estimators Improve Model Generalization. CoRR Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Deepta Rajan, Andreas Spanias
2021	J	`jnl`	On the role of artificial intelligence in medical imaging of COVID-19. Patterns Jannis Born, David Beymer, Deepta Rajan, Adam Coy, Vandana V. Mukherjee, Matteo Manica, Prasanth Prasanna, Deddeh Ballah, Michal Guindy, Dorith Shaham, Pallav L. Shah, Emmanouil Karteris, Jan L. Robertus, Maria Gabrani, Michal Rosen-Zvi
2021	J	`jnl`	On the role of artificial intelligence in medical imaging of COVID-19. Patterns Jannis Born, David Beymer, Deepta Rajan, Adam Coy, Vandana V. Mukherjee, Matteo Manica, Prasanth Prasanna, Deddeh Ballah, Michal Guindy, Dorith Shaham, Pallav L. Shah, Emmanouil Karteris, Jan L. Robertus, Maria Gabrani, Michal Rosen-Zvi
2021	—	`conf`	Self-training with improved regularization for sample-efficient chest x-ray classification. Computer-Aided Diagnosis Deepta Rajan, Jayaraman J. Thiagarajan, Alexandros Karargyris, Satyananda Kashyap
2020	—	`conf`	Automatic Diagnosis of Pulmonary Embolism Using an Attention-guided Framework: A Large-scale Study. MIDL Luyao Shi, Deepta Rajan, Shafiq Abedin, Manikanta Srikar Yellapragada, David Beymer, Ehsan Dehghan
2020	J	`jnl`	Automatic Diagnosis of Pulmonary Embolism Using an Attention-guided Framework: A Large-scale Study. CoRR Luyao Shi, Deepta Rajan, Shafiq Abedin, Manikanta Srikar Yellapragada, David Beymer, Ehsan Dehghan
2020	J	`jnl`	Calibrating Healthcare AI: Towards Reliable and Interpretable Deep Predictive Models. CoRR Jayaraman J. Thiagarajan, Prasanna Sattigeri, Deepta Rajan, Bindya Venkatesh
2020	—	`conf`	Improving Reliability of Clinical Models Using Prediction Calibration. UNSURE/GRAIL@MICCAI Jayaraman J. Thiagarajan, Bindya Venkatesh, Deepta Rajan, Prasanna Sattigeri
2020	Misc	`conf`	Learn-By-Calibrating: Using Calibration As A Training Objective. ICASSP Jayaraman J. Thiagarajan, Bindya Venkatesh, Deepta Rajan
2020	J	`jnl`	Self-Training with Improved Regularization for Few-Shot Chest X-Ray Classification. CoRR Deepta Rajan, Jayaraman J. Thiagarajan, Alexandros Karargyris, Satyananda Kashyap
2019	J	`jnl`	Generalization Studies of Neural Network Models for Cardiac Disease Detection Using Limited Channel ECG. CoRR Deepta Rajan, David Beymer, Girish Narayan
2019	J	`jnl`	Learn-By-Calibrating: Using Calibration as a Training Objective. CoRR Jayaraman J. Thiagarajan, Bindya Venkatesh, Deepta Rajan
2019	—	`conf`	Leveraging Medical Visual Question Answering with Supporting Facts. CLEF (Working Notes) Tomasz Kornuta, Deepta Rajan, Chaitanya Shivade, Alexis Asseman, Ahmet S. Ozcan
2019	J	`jnl`	Leveraging Medical Visual Question Answering with Supporting Facts. CoRR Tomasz Kornuta, Deepta Rajan, Chaitanya Shivade, Alexis Asseman, Ahmet S. Ozcan
2019	—	`conf`	Pi-PE: A Pipeline for Pulmonary Embolism Detection using Sparsely Annotated 3D CT Images. ML4H@NeurIPS Deepta Rajan, David Beymer, Shafiqul Abedin, Ehsan Dehghan
2019	J	`jnl`	Pi-PE: A Pipeline for Pulmonary Embolism Detection using Sparsely Annotated 3D CT Images. CoRR Deepta Rajan, David Beymer, Shafiqul Abedin, Ehsan Dehghan
2018	—	`conf`	A Generative Modeling Approach to Limited Channel ECG Classification. EMBC Deepta Rajan, Jayaraman J. Thiagarajan
2018	J	`jnl`	A Generative Modeling Approach to Limited Channel ECG Classification. CoRR Deepta Rajan, Jayaraman J. Thiagarajan
2018	A*	`conf`	Attend and Diagnose: Clinical Time Series Analysis Using Attention Models. AAAI Huan Song, Deepta Rajan, Jayaraman J. Thiagarajan, Andreas Spanias
2018	J	`jnl`	Can Deep Clinical Models Handle Real-World Domain Shifts? CoRR Jayaraman J. Thiagarajan, Deepta Rajan, Prasanna Sattigeri
2018	—	`conf`	Improving Generalization of Deep Models for Cardiac Disease Detection Using Limited Channel ECG. CinC Deepta Rajan, David Beymer, Girish Narayan
2017	J	`jnl`	Attend and Diagnose: Clinical Time Series Analysis using Attention Models. CoRR Huan Song, Deepta Rajan, Jayaraman J. Thiagarajan, Andreas Spanias
2016	—	`conf`	Identifying Patients at Risk for Aortic Stenosis Through Learning from Multimodal Data. MICCAI (3) Tanveer F. Syeda-Mahmood, Yanrong Guo, Mehdi Moradi, David Beymer, Deepta Rajan, Yu Cao, Yaniv Gur, Mohammadreza Negahdar
2016	—	`conf`	Medical sieve: a cognitive assistant for radiologists and cardiologists. Computer-Aided Diagnosis Tanveer F. Syeda-Mahmood, Eugene Walach, David Beymer, Flora Gilboa-Solomon, Mehdi Moradi, Pavel Kisilev, Deepika Kakrania, Colin B. Compas, Hongzhi Wang, Mohammadreza Negahdar, Yu Cao, Tyler Baldwin, Yufan Guo, Yaniv Gur, Deepta Rajan, Aviad Zlotnick, Simona Rabinovici-Cohen, Rami Ben-Ari, Guy Amit, Prasanth Prasanna, J. Morey, Orest B. Boyko, Sharbell Y. Hashoul
2014	C	`conf`	Embedding Android signal processing apps in a high school math class - An RET project. FIE Mahesh K. Banavar, Deepta Rajan, Andrew Strom, Photini Spanias, Xue Sophia Zhang, Henry Braun, Andreas Spanias
2014	J	`jnl`	Kernel Sparse Models for Automated Tumor Segmentation. Int. J. Artif. Intell. Tools Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Deepta Rajan, Andreas Spanias, Anup Puri, David H. Frakes
2013	C	`conf`	Health monitoring laboratories by interfacing physiological sensors to mobile android devices. FIE Deepta Rajan, Andreas Spanias, Suhas Ranganath, Mahesh K. Banavar, Photini Spanias
2013	J	`jnl`	Kernel Sparse Models for Automated Tumor Segmentation CoRR Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Deepta Rajan, Anup Puri, David H. Frakes, Andreas Spanias
2012	C	`conf`	Automated tumor segmentation using kernel sparse representations. BIBE Jayaraman J. Thiagarajan, Deepta Rajan, Karthikeyan Natesan Ramamurthy, David H. Frakes, Andreas Spanias