Predicting Mechanical Ventilation Requirement and Mortality in COVID-19 using Radiomics and Deep Learning on Chest Radiographs: A Multi-Institutional Study. - Joseph Bae; Saarthak Kapse; Gagandeep Singh; Tej Phatak; Jeremy Green; Nikhil Madan; Prateek Prasanna (CoRR, 2020)

Digital Landscape of COVID-19 Testing: Challenges and Opportunities. - Darshan Gandhi; Rohan Sukumaran; Priyanshi Katiyar; Alex Radunsky; Sunaina Anand; Shailesh Advani; Jil Kothari; Kasia Jakimowicz; Sheshank Shankar; Sethuraman T. V.; Krutika Misra; Aishwarya Saxena; et al. (CoRR, 2020)

Evolution of chest radiograph radiomics and association with respiratory and inflammatory parameters in COVID-19 patients undergoing prone ventilation: preliminary findings. - Connor Cowan; Joseph Bae; Gagandeep Singh; Rohit Khullar; Shrey Shah; Nikhil Madan; Prateek Prasanna (Computer-Aided Diagnosis, 2021)

Attention-Based Multi-scale Gated Recurrent Encoder with Novel Correlation Loss for COVID-19 Progression Prediction. - Aishik Konwer; Joseph Bae; Gagandeep Singh; Rishabh Gattu; Syed Ali; Jeremy Green; Tej Phatak; Prateek Prasanna (MICCAI (5), 2021)

Chest Radiograph Disentanglement for COVID-19 Outcome Prediction. - Lei Zhou; Joseph Bae; Huidong Liu; Gagandeep Singh; Jeremy Green; Dimitris Samaras; Prateek Prasanna (MICCAI (7), 2021)

Predicting COVID-19 Lung Infiltrate Progression on Chest Radiographs Using Spatio-temporal LSTM based Encoder-Decoder Network. - Aishik Konwer; Joseph Bae; Gagandeep Singh; Rishabh Gattu; Syed Ali; Jeremy Green; Tej Phatak; Amit Gupta; Chao Chen 012; Joel H. Saltz; Prateek Prasanna (MIDL, 2021)

COVID-19 Tests Gone Rogue: Privacy, Efficacy, Mismanagement and Misunderstandings. - Manuel Morales; Rachel Barbar; Darshan Gandhi; Sanskruti Landage; Joseph Bae; Arpita Vats; Jil Kothari; Sheshank Shankar; Rohan Sukumaran; Himi Mathur; Krutika Misra; Aishwarya Saxena; et al. (CoRR, 2021)

MIT SafePaths Card (MiSaCa): Augmenting Paper Based Vaccination Cards with Printed Codes. - Joseph Bae; Rohan Sukumaran; Sheshank Shankar; Saurish Srivastava; Rohan Iyer; Aryan Mahindra; Qamil Mirza; Maurizio Arseni; Anshuman Sharma; Saras Agrawal; Orna Mukhopadhyay; Colin Kang; et al. (CoRR, 2021)

COVID-19 Outbreak Prediction and Analysis using Self Reported Symptoms. - Rohan Sukumaran; Parth Patwa; T. V. Sethuraman; Sheshank Shankar; Rishank Kanaparti; Joseph Bae; Yash Mathur; Abhishek Singh 005; Ayush Chopra; Myungsun Kang; Priya Ramaswamy; Ramesh Raskar (CoRR, 2021)

Mobile Apps Prioritizing Privacy, Efficiency and Equity: A Decentralized Approach to COVID-19 Vaccination Coordination. - Joseph Bae; Rohan Sukumaran; Sheshank Shankar; Anshuman Sharma; Ishaan Singh; Haris Nazir; Colin Kang; Saurish Srivastava; Parth Patwa; Abhishek Singh 005; Priyanshi Katiyar; Vitor Pamplona; et al. (CoRR, 2021)

Temporal Context Matters: Enhancing Single Image Prediction with Disease Progression Representations. - Aishik Konwer; Xuan Xu; Joseph Bae; Chao Chen 012; Prateek Prasanna (CVPR, 2022)

Lung Swapping Autoencoder: Learning a Disentangled Structure-texture Representation of Chest Radiographs. - Lei Zhou; Joseph Bae; Huidong Liu; Gagandeep Singh; Jeremy Green; Amit Gupta; Dimitris Samaras; Prateek Prasanna (CoRR, 2022)

Self Pre-training with Masked Autoencoders for Medical Image Analysis. - Lei Zhou; Huidong Liu; Joseph Bae; Junjun He; Dimitris Samaras; Prateek Prasanna (CoRR, 2022)

Enhancing Modality-Agnostic Representations via Meta-learning for Brain Tumor Segmentation. - Aishik Konwer; Xiaoling Hu 002; Joseph Bae; Xuan Xu; Chao Chen 012; Prateek Prasanna (ICCV, 2023)

Token Sparsification for Faster Medical Image Segmentation. - Lei Zhou; Huidong Liu; Joseph Bae; Junjun He; Dimitris Samaras; Prateek Prasanna (IPMI, 2023)

Self Pre-Training with Masked Autoencoders for Medical Image Classification and Segmentation. - Lei Zhou; Huidong Liu; Joseph Bae; Junjun He; Dimitris Samaras; Prateek Prasanna (ISBI, 2023)

Context-Aware Sit-Stand Desk for Promoting Healthy and Productive Behaviors. - Donghan Hu; Joseph Bae; Sol Ie Lim; Sang Won Lee 002 (UIST (Adjunct Volume), 2023)

SAMU: An Efficient and Promptable Foundation Model for Medical Image Segmentation. - Joseph Bae; Xueqi Guo; Halid Ziya Yerebakan; Yoshihisa Shinagawa; Sepehr Farhand (MedAGI@MICCAI, 2024)

HoG-Net: Hierarchical Multi-organ Graph Network for Head and Neck Cancer Recurrence Prediction from CT Images. - Joseph Bae; Saarthak Kapse; Lei Zhou; Kartik Mani; Prateek Prasanna (MICCAI (5), 2024)