Machine Learning for Health (ML4H) 2023

Stefan Hegselmann, Antonio Parziale, Divya Shanmugam, Shengpu Tang, Kristen Severson, Mercy Nyamewaa Asiedu, Serina Chang, Bonaventure F. P. Dossou, Qian Huang, Fahad Kamran, Haoran Zhang, Sujay Nagaraj, Luis Oala, Shan Xu, Chinasa T. Okolo, Helen Zhou, Jessica Dafflon, Caleb Ellington, Sarah Jabbour, Hyewon Jeong, Harry Reyes Nieva, Yuzhe Yang, Ghada Zamzmi, Vishwali Mhasawade, Van Truong, Payal Chandak, Matthew Lee, Peniel Argaw, Kyle Heuton, Harvineet Singh, Thomas Hartvigsen; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:1-12

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Towards Equitable Kidney Tumor Segmentation: Bias Evaluation and Mitigation

Muhammad Muneeb Afzal, Muhammad Osama Khan, Shujaat Mirza; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:13-26

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Representing visual classification as a linear combination of words

Shobhit Agarwal, Yevgeniy R. Semenov, William Lotter; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:27-38

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Learning Temporal Higher-order Patterns to Detect Anomalous Brain Activity

Ali Behrouz, Farnoosh Hashemi; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:39-51

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Multi-modal Graph Learning over UMLS Knowledge Graphs

Manuel Burger, Gunnar Rätsch, Rita Kuznetsova; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:52-81

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LLMs Accelerate Annotation for Medical Information Extraction

Akshay Goel, Almog Gueta, Omry Gilon, Chang Liu, Sofia Erell, Lan Huong Nguyen, Xiaohong Hao, Bolous Jaber, Shashir Reddy, Rupesh Kartha, Jean Steiner, Itay Laish, Amir Feder; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:82-100

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Towards Reliable Dermatology Evaluation Benchmarks

Fabian Gröger, Simone Lionetti, Philippe Gottfrois, Alvaro Gonzalez-Jimenez, Matthew Groh, Roxana Daneshjou, Labelling Consortium, Alexander A. Navarini, Marc Pouly; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:101-128

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A Probabilistic Method to Predict Classifier Accuracy on Larger Datasets given Small Pilot Data

Ethan Harvey, Wansu Chen, David M. Kent, Michael C. Hughes; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:129-144

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Curriculum Self-Supervised Learning for 3D CT Cardiac Image Segmentation

Mohammad Reza Hosseinzadeh Taher, Masaki Ikuta, Ravi Soni; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:145-156

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REMEDI: REinforcement learning-driven adaptive MEtabolism modeling of primary sclerosing cholangitis DIsease progression

Chang Hu, Krishnakant V. Saboo, Ahmad H. Ali, Brian D. Juran, Konstantinos N. Lazaridis, Ravishankar K. Iyer; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:157-189

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Activation From Sparse 2D Cardiac MRIs

Nivetha Jayakumar, Jiarui Xing, Tonmoy Hossain, Fred Epstein, Kenneth Bilchick, Miaomiao Zhang; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:190-200

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NoteContrast: Contrastive Language-Diagnostic Pretraining for Medical Text

Prajwal Kailas, Max Homilius, Rahul C. Deo, Calum A. MacRae; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:201-216

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How Fair are Medical Imaging Foundation Models?

Muhammad Osama Khan, Muhammad Muneeb Afzal, Shujaat Mirza, Yi Fang; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:217-231

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Learning Generalized Medical Image Representations Through Image-Graph Contrastive Pretraining

Sameer Khanna, Daniel Michael, Marinka Zitnik, Pranav Rajpurkar; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:232-243

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Multimodal Pretraining of Medical Time Series and Notes

Ryan King, Tianbao Yang, Bobak J. Mortazavi; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:244-255

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Deep Multimodal Fusion for Surgical Feedback Classification

Rafal Kocielnik, Elyssa Y. Wong, Timothy N. Chu, Lydia Lin, De-An Huang, Jiayun Wang, Anima Anandkumar, Andrew J. Hung; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:256-267

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On the Importance of Step-wise Embeddings for Heterogeneous Clinical Time-Series

Rita Kuznetsova, Alizée Pace, Manuel Burger, Hugo Yèche, Gunnar Rätsch; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:268-291

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Gradient-Map-Guided Adaptive Domain Generalization for Cross Modality MRI Segmentation

Bingnan Li, Zhitong Gao, Xuming He; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:292-306

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Anytime-valid inference in N-of-1 trials

Ivana Malenica, Yongyi Guo, Kyra Gan, Stefan Konigorski; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:307-322

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Compositional Q-learning for electrolyte repletion with imbalanced patient sub-populations

Aishwarya Mandyam, Andrew Jones, Jiayu Yao, Krzysztof Laudanski, Barbara E. Engelhardt; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:323-339

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Designing and evaluating an online reinforcement learning agent for physical exercise recommendations in N-of-1 trials

Dominik Meier, Ipek Ensari, Stefan Konigorski; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:340-352

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Med-Flamingo: a Multimodal Medical Few-shot Learner

Michael Moor, Qian Huang, Shirley Wu, Michihiro Yasunaga, Yash Dalmia, Jure Leskovec, Cyril Zakka, Eduardo Pontes Reis, Pranav Rajpurkar; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:353-367

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Supervised Electrocardiogram(ECG) Features Outperform Knowledge-based And Unsupervised Features In Individualized Survival Prediction

Yousef Nademi, Sunil V Kalmady, Weijie Sun, Shi-ang Qi, Abram Hindle, Padma Kaul, Russell Greiner; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:368-384

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Pragmatic Radiology Report Generation

Dang Nguyen, Chacha Chen, He He, Chenhao Tan; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:385-402

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Temporal Supervised Contrastive Learning for Modeling Patient Risk Progression

Shahriar Noroozizadeh, Jeremy C. Weiss, George H. Chen; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:403-427

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Nonparametric modeling of the composite effect of multiple nutrients on blood glucose dynamics

Arina Odnoblyudova, Caglar Hizli, ST John, Andrea Cognolato, Anne Juuti, Simo Särkkä, Kirsi Pietiläinen, Pekka Marttinen; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:428-444

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Using Reinforcement Learning for Multi-Objective Cluster-Level Optimization of Non-Pharmaceutical Interventions for Infectious Disease

Xueqiao Peng, Jiaqi Xu, Xi Chen, Dinh Song An Nguyen, Andrew Perrault; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:445-460

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Mixture of Coupled HMMs for Robust Modeling of Multivariate Healthcare Time Series

Onur Poyraz, Pekka Marttinen; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:461-479

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Automated Cardiovascular Record Retrieval by Multimodal Learning between Electrocardiogram and Clinical Report

Jielin Qiu, Jiacheng Zhu, Shiqi Liu, William Han, Jingqi Zhang, Chaojing Duan, Michael A. Rosenberg, Emerson Liu, Douglas Weber, Ding Zhao; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:480-497

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MULTIPAR: Supervised Irregular Tensor Factorization with Multi-task Learning for Computational Phenotyping

Yifei Ren, Jian Lou, Li Xiong, Joyce C Ho, Xiaoqian Jiang, Sivasubramanium Venkatraman Bhavani; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:498-511

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Robust semi-supervised segmentation with timestep ensembling diffusion models

Margherita Rosnati, Mélanie Roschewitz, Ben Glocker; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:512-527

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LymphoML: An interpretable artificial intelligence-based method identifies morphologic features that correlate with lymphoma subtype

Vivek Shankar, Xiaoli Yang, Vrishab Krishna, Brent Tan, Oscar Silva, Rebecca Rojansky, Andrew Ng, Fabiola Valvert, Edward Briercheck, David Weinstock, Yasodha Natkunam, Sebastian Fernandez-Pol, Pranav Rajpurkar; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:528-558

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Eigen: Expert-Informed Joint Learning Aggregation for High-Fidelity Information Extraction from Document Images

Abhishek Singh, Venkatapathy Subramanian, Ayush Maheshwari, Pradeep Narayan, Devi Prasad Shetty, Ganesh Ramakrishnan; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:559-573

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Interpretable Survival Analysis for Heart Failure Risk Prediction

Mike Van Ness, Tomas Bosschieter, Natasha Din, Andrew Ambrosy, Alexander Sandhu, Madeleine Udell; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:574-593

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GANcMRI: Cardiac magnetic resonance video generation and physiologic guidance using latent space prompting

Milos Vukadinovic, Alan C Kwan, Debiao Li, David Ouyang; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:594-606

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Interpretable Mechanistic Representations for Meal-level Glycemic Control in the Wild

Ke Alexander Wang, Emily B. Fox; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:607-622

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TransEHR: Self-Supervised Transformer for Clinical Time Series Data

Yanbo Xu, Shangqing Xu, Manav Ramprassad, Alexey Tumanov, Chao Zhang; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:623-635

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Dynamic Interpretable Change Point Detection for Physiological Data Analysis

Jennifer Yu, Tina Behrouzi, Kopal Garg, Anna Goldenberg, Sana Tonekaboni; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:636-649

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Zero-Shot ECG Diagnosis with Large Language Models and Retrieval-Augmented Generation

Han Yu, Peikun Guo, Akane Sano; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:650-663

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Diffusion Model-Based Data Augmentation for Lung Ultrasound Classification with Limited Data

Xiaohui Zhang, Ahana Gangopadhyay, Hsi-Ming Chang, Ravi Soni; Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:664-676

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