Machine Learning for Health (ML4H) 2022

Antonio Parziale, Monica Agrawal, Shengpu Tang, Kristen Severson, Luis Oala, Adarsh Subbaswamy, Sayantan Kumar, Elora Schoerverth, Stefan Hegselmann, Helen Zhou, Ghada Zamzmi, Purity Mugambi, Elena Sizikova, Girmaw Abebe Tadesse, Yuyin Zhou, Taylor Killian, Haoran Zhang, Fahad Kamran, Andrea Hobby, Mars Huang, Ahmed Alaa, Harvineet Singh, Irene Y. Chen, Shalmali Joshi; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:1-11

[abs][Download PDF]

Imputation Strategies Under Clinical Presence: Impact on Algorithmic Fairness

Vincent Jeanselme, Maria De-Arteaga, Zhe Zhang, Jessica Barrett, Brian Tom; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:12-34

[abs][Download PDF][Software]

Predicting Treatment Adherence of Tuberculosis Patients at Scale

Mihir Kulkarni, Satvik Golechha, Rishi Raj, Jithin K. Sreedharan, Ankit Bhardwaj, Santanu Rathod, Bhavin Vadera, Jayakrishna Kurada, Sanjay Mattoo, Rajendra Joshi, Kirankumar Rade, Alpan Raval; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:35-61

[abs][Download PDF]

Distributionally Robust Survival Analysis: A Novel Fairness Loss Without Demographics

Shu Hu, George H. Chen; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:62-87

[abs][Download PDF][Software]

mmVAE: multimorbidity clustering using Relaxed Bernoulli $β$-Variational Autoencoders

Charles Gadd, Krishnarajah Nirantharakumar, Christopher Yau; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:88-102

[abs][Download PDF][Software][Supplementary PDF]

Feature Allocation Approach for Multimorbidity Trajectory Modelling

Woojung Kim, Paul A. Jenkins, Christopher Yau; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:103-119

[abs][Download PDF][Software]

Towards Cross-Modal Causal Structure and Representation Learning

Haiyi Mao, Hongfu Liu, Jason Xiaotian Dou, Panayiotis V. Benos; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:120-140

[abs][Download PDF]

Identifying Heterogeneous Treatment Effects in Multiple Outcomes using Joint Confidence Intervals

Peniel N. Argaw, Elizabeth Healey, Isaac S. Kohane; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:141-170

[abs][Download PDF][Software]

Meta-analysis of individualized treatment rules via sign-coherency

Jay Jojo Cheng, Jared D. Huling, Guanhua Chen; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:171-198

[abs][Download PDF][Software]

SleepQA: A Health Coaching Dataset on Sleep for Extractive Question Answering

Iva Bojic, Qi Chwen Ong, Megh Thakkar, Esha Kamran, Irving Yu Le Shua, Jaime Rei Ern Pang, Jessica Chen, Vaaruni Nayak, Shafiq Joty, Josip Car; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:199-217

[abs][Download PDF][Software]

Extend and Explain: Interpreting Very Long Language Models

Joel Stremmel, Brian L. Hill, Jeffrey Hertzberg, Jaime Murillo, Llewelyn Allotey, Eran Halperin; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:218-258

[abs][Download PDF][Software]

Counterfactual and Factual Reasoning over Hypergraphs for Interpretable Clinical Predictions on EHR

Ran Xu, Yue Yu, Chao Zhang, Mohammed K Ali, Joyce C Ho, Carl Yang; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:259-278

[abs][Download PDF][Software]

Neurodevelopmental Phenotype Prediction: A State-of-the-Art Deep Learning Model

Dániel Unyi, Bálint Gyires-Tóth; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:279-289

[abs][Download PDF][Software]

Analysing the effectiveness of a generative model for semi-supervised medical image segmentation

Margherita Rosnati, Fabio De Sousa Ribeiro, Miguel Monteiro, Daniel Coelho de Castro, Ben Glocker; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:290-310

[abs][Download PDF]

An Extensive Data Processing Pipeline for MIMIC-IV

Mehak Gupta, Brennan Gallamoza, Nicolas Cutrona, Pranjal Dhakal, Raphael Poulain, Rahmatollah Beheshti; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:311-325

[abs][Download PDF][Software]

Predicting attrition patterns from pediatric weight management programs

Hamed Fayyaz, Thao-Ly T. Phan, H. Timothy Bunnell, Rahmatollah Beheshti; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:326-342

[abs][Download PDF][Software]

Automated LOINC Standardization Using Pre-trained Large Language Models

Tao Tu, Eric Loreaux, Emma Chesley, Adam D. Lelkes, Paul Gamble, Mathias Bellaiche, Martin Seneviratne, Ming-Jun Chen; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:343-355

[abs][Download PDF]

An Empirical Study on Activity Recognition in Long Surgical Videos

Zhuohong He, Ali Mottaghi, Aidean Sharghi, Muhammad Abdullah Jamal, Omid Mohareri; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:356-372

[abs][Download PDF]

OSLAT: Open Set Label Attention Transformer for Medical Entity Retrieval and Span Extraction

Raymond Li, Ilya Valmianski, Li Deng, Xavier Amatriain, Anitha Kannan; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:373-390

[abs][Download PDF][Software]

Adapting Pre-trained Vision Transformers from 2D to 3D through Weight Inflation Improves Medical Image Segmentation

Yuhui Zhang, Shih-Cheng Huang, Zhengping Zhou, Matthew P. Lungren, Serena Yeung; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:391-404

[abs][Download PDF][Software][Supplementary PDF]

Hyper-AdaC: Adaptive clustering-based hypergraph representation of whole slide images for survival analysis

Hakim Benkirane, Maria Vakalopoulou, Stergios Christodoulidis, Ingrid-Judith Garberis, Stefan Michiels, Paul-Henry Cournède; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:405-418

[abs][Download PDF][Software]

Differentiable programming for functional connectomics

Rastko Ciric, Armin W. Thomas, Oscar Esteban, Russell A. Poldrack; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:419-455

[abs][Download PDF][Software]

Improving Radiology Report Generation Systems by Removing Hallucinated References to Non-existent Priors

Vignav Ramesh, Nathan A. Chi, Pranav Rajpurkar; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:456-473

[abs][Download PDF][Software]

Improving Sepsis Prediction Model Generalization With Optimal Transport

Jie Wang, Ronald Moore, Yao Xie, Rishikesan Kamaleswaran; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:474-488

[abs][Download PDF]

A Path Towards Clinical Adaptation of Accelerated MRI

Michael S. Yao, Michael S. Hansen; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:489-511

[abs][Download PDF][Software]

Machine and Deep Learning Methods for Predicting Immune Checkpoint Blockade Response

Danliang Ho, Mehul Motani; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:512-529

[abs][Download PDF]

Deep Kernel Learning with Temporal Gaussian Processes for Clinical Variable Prediction in Alzheimer’s Disease

Vasiliki Tassopoulou, Fanyang Yu, Christos Davatzikos; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:539-551

[abs][Download PDF]

Instability in clinical risk stratification models using deep learning

Daniel Lopez-Martinez, Alex Yakubovich, Martin Seneviratne, Adam D. Lelkes, Akshit Tyagi, Jonas Kemp, Ethan Steinberg, N. Lance Downing, Ron C. Li, Keith E. Morse, Nigam H. Shah, Ming-Jun Chen; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:552-565

[abs][Download PDF]

A for-loop is all you need. For solving the inverse problem in the case of personalized tumor growth modeling

Ivan Ezhov, Marcel Rosier, Lucas Zimmer, Florian Kofler, Suprosanna Shit, Johannes C. Paetzold, Kevin Scibilia, Felix Steinbauer, Leon Maechler, Katharina Franitza, Tamaz Amiranashvili, Martin J. Menten, Marie Metz, Sailesh Conjeti, Benedikt Wiestler, Bjoern Menze; Proceedings of the 2nd Machine Learning for Health symposium, PMLR 193:566-577

[abs][Download PDF][Software]