Deepta Rajan

Publication Activity (10 Years)

Years Active: 2012-2023
Publications (10 Years): 32

Top Topics

Machine Learning Models

Top Venues

Medical Imaging: Computer-Aided Diagnosis

Publications

Vivek Sivaraman Narayanaswamy, Yamen Mubarka, Rushil Anirudh, Deepta Rajan, Jayaraman J. Thiagarajan
Exploring Inlier and Outlier Specification for Improved Medical OOD Detection. ICCV (Workshops) (2023)
Vivek Sivaraman Narayanaswamy, Yamen Mubarka, Rushil Anirudh, Deepta Rajan, Andreas Spanias, Jayaraman J. Thiagarajan
Know Your Space: Inlier and Outlier Construction for Calibrating Medical OOD Detectors. MIDL (2023)
Vivek Sivaraman Narayanaswamy, Yamen Mubarka, Rushil Anirudh, Deepta Rajan, Andreas Spanias, Jayaraman J. Thiagarajan
Revisiting Inlier and Outlier Specification for Improved Out-of-Distribution Detection. CoRR (2022)
Jin Li, Deepta Rajan, Chintan Shah, Dinkar Juyal, Shreya Chakraborty, Chandan Akiti, Filip Kos, Janani Iyer, Anand Sampat, Ali Behrooz
Self-training of Machine Learning Models for Liver Histopathology: Generalization under Clinical Shifts. CoRR (2022)
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
On the role of artificial intelligence in medical imaging of COVID-19. Patterns 2 (6) (2021)
Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Deepta Rajan, Andreas Spanias
Loss Estimators Improve Model Generalization. CoRR (2021)
Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Deepta Rajan, Jia Liang, Akshay Chaudhari, Andreas Spanias
Designing Counterfactual Generators using Deep Model Inversion. NeurIPS (2021)
Deepta Rajan, Jayaraman J. Thiagarajan, Alexandros Karargyris, Satyananda Kashyap
Self-training with improved regularization for sample-efficient chest x-ray classification. Medical Imaging: Computer-Aided Diagnosis (2021)
Yiting Xie, Deepta Rajan, Larissa C. Schudlo, Yusuke Takeuchi, Benedikt Graf, Adam Coy, Mohammadreza Negahdar, Vandana V. Mukherjee, David Beymer, Arun Krishnan
Automatic localization of lung opacity in chest CT images: a real-world study. Medical Imaging: Computer-Aided Diagnosis (2021)
Joshua K. Lee, Yuheng Bu, Deepta Rajan, Prasanna Sattigeri, Rameswar Panda, Subhro Das, Gregory W. Wornell
Fair Selective Classification Via Sufficiency. ICML (2021)
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
On the role of artificial intelligence in medical imaging of COVID-19. Patterns 2 (8) (2021)
Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Deepta Rajan, Jason Liang, Akshay Chaudhari, Andreas Spanias
Designing Counterfactual Generators using Deep Model Inversion. CoRR (2021)
Luyao Shi, Deepta Rajan, Shafiq Abedin, Manikanta Srikar Yellapragada, David Beymer, Ehsan Dehghan
Automatic Diagnosis of Pulmonary Embolism Using an Attention-guided Framework: A Large-scale Study. MIDL (2020)
Deepta Rajan, Jayaraman J. Thiagarajan, Alexandros Karargyris, Satyananda Kashyap
Self-Training with Improved Regularization for Few-Shot Chest X-Ray Classification. CoRR (2020)
Luyao Shi, Deepta Rajan, Shafiq Abedin, Manikanta Srikar Yellapragada, David Beymer, Ehsan Dehghan
Automatic Diagnosis of Pulmonary Embolism Using an Attention-guided Framework: A Large-scale Study. CoRR (2020)
Jayaraman J. Thiagarajan, Bindya Venkatesh, Deepta Rajan, Prasanna Sattigeri
Improving Reliability of Clinical Models Using Prediction Calibration. UNSURE/GRAIL@MICCAI (2020)
Jayaraman J. Thiagarajan, Bindya Venkatesh, Deepta Rajan
Learn-By-Calibrating: Using Calibration As A Training Objective. ICASSP (2020)
Jayaraman J. Thiagarajan, Prasanna Sattigeri, Deepta Rajan, Bindya Venkatesh
Calibrating Healthcare AI: Towards Reliable and Interpretable Deep Predictive Models. CoRR (2020)
Jayaraman J. Thiagarajan, Bindya Venkatesh, Deepta Rajan
Learn-By-Calibrating: Using Calibration as a Training Objective. CoRR (2019)
Deepta Rajan, David Beymer, Girish Narayan
Generalization Studies of Neural Network Models for Cardiac Disease Detection Using Limited Channel ECG. CoRR (2019)
Deepta Rajan, David Beymer, Shafiqul Abedin, Ehsan Dehghan
Pi-PE: A Pipeline for Pulmonary Embolism Detection using Sparsely Annotated 3D CT Images. ML4H@NeurIPS (2019)
Deepta Rajan, David Beymer, Shafiqul Abedin, Ehsan Dehghan
Pi-PE: A Pipeline for Pulmonary Embolism Detection using Sparsely Annotated 3D CT Images. CoRR (2019)
Tomasz Kornuta, Deepta Rajan, Chaitanya Shivade, Alexis Asseman, Ahmet S. Ozcan
Leveraging Medical Visual Question Answering with Supporting Facts. CoRR (2019)
Tomasz Kornuta, Deepta Rajan, Chaitanya Shivade, Alexis Asseman, Ahmet S. Ozcan
Leveraging Medical Visual Question Answering with Supporting Facts. CLEF (Working Notes) (2019)
Deepta Rajan, Jayaraman J. Thiagarajan
A Generative Modeling Approach to Limited Channel ECG Classification. EMBC (2018)
Huan Song, Deepta Rajan, Jayaraman J. Thiagarajan, Andreas Spanias
Attend and Diagnose: Clinical Time Series Analysis Using Attention Models. AAAI (2018)
Deepta Rajan, Jayaraman J. Thiagarajan
A Generative Modeling Approach to Limited Channel ECG Classification. CoRR (2018)
Deepta Rajan, David Beymer, Girish Narayan
Improving Generalization of Deep Models for Cardiac Disease Detection Using Limited Channel ECG. CinC (2018)
Jayaraman J. Thiagarajan, Deepta Rajan, Prasanna Sattigeri
Can Deep Clinical Models Handle Real-World Domain Shifts? CoRR (2018)
Huan Song, Deepta Rajan, Jayaraman J. Thiagarajan, Andreas Spanias
Attend and Diagnose: Clinical Time Series Analysis using Attention Models. CoRR (2017)
Tanveer F. Syeda-Mahmood, Yanrong Guo, Mehdi Moradi, David Beymer, Deepta Rajan, Yu Cao, Yaniv Gur, Mohammadreza Negahdar
Identifying Patients at Risk for Aortic Stenosis Through Learning from Multimodal Data. MICCAI (3) (2016)
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
Medical sieve: a cognitive assistant for radiologists and cardiologists. Medical Imaging: Computer-Aided Diagnosis (2016)
Mahesh K. Banavar, Deepta Rajan, Andrew Strom, Photini Spanias, Xue Sophia Zhang, Henry Braun, Andreas Spanias
Embedding Android signal processing apps in a high school math class - An RET project. FIE (2014)
Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Deepta Rajan, Andreas Spanias, Anup Puri, David H. Frakes
Kernel Sparse Models for Automated Tumor Segmentation. Int. J. Artif. Intell. Tools 23 (3) (2014)
Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Deepta Rajan, Anup Puri, David H. Frakes, Andreas Spanias
Kernel Sparse Models for Automated Tumor Segmentation CoRR (2013)
Deepta Rajan, Andreas Spanias, Suhas Ranganath, Mahesh K. Banavar, Photini Spanias
Health monitoring laboratories by interfacing physiological sensors to mobile android devices. FIE (2013)
Jayaraman J. Thiagarajan, Deepta Rajan, Karthikeyan Natesan Ramamurthy, David H. Frakes, Andreas Spanias
Automated tumor segmentation using kernel sparse representations. BIBE (2012)