Table of Contents

• Machine Learning for Health (ML4H) 2023Stefan 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. 1-12 [doi]
• Towards Equitable Kidney Tumor Segmentation: Bias Evaluation and MitigationMuhammad Muneeb Afzal, Muhammad Osama Khan, Shujaat Mirza. 13-26 [doi]
• Representing visual classification as a linear combination of wordsShobhit Agarwal, Yevgeniy R. Semenov, William Lotter. 27-38 [doi]
• Learning Temporal Higher-order Patterns to Detect Anomalous Brain ActivityAli Behrouz, Farnoosh Hashemi. 39-51 [doi]
• Multi-modal Graph Learning over UMLS Knowledge GraphsManuel Burger, Gunnar Rätsch, Rita Kuznetsova. 52-81 [doi]
• LLMs Accelerate Annotation for Medical Information ExtractionAkshay 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. 82-100 [doi]
• Towards Reliable Dermatology Evaluation BenchmarksFabian Gröger, Simone Lionetti, Philippe Gottfrois, Álvaro González-Jiménez, Matthew Groh, Roxana Daneshjou, Labelling Consortium, Alexander A. Navarini, Marc Pouly. 101-128 [doi]
• A Probabilistic Method to Predict Classifier Accuracy on Larger Datasets given Small Pilot DataEthan Harvey, Wansu Chen, David M. Kent, Michael C. Hughes. 129-144 [doi]
• Curriculum Self-Supervised Learning for 3D CT Cardiac Image SegmentationMohammad Reza Hosseinzadeh Taher, Masaki Ikuta, Ravi Soni. 145-156 [doi]
• REMEDI: REinforcement learning-driven adaptive MEtabolism modeling of primary sclerosing cholangitis DIsease progressionChang Hu, Krishnakant V. Saboo, Ahmad H. Ali, Brian D. Juran, Konstantinos N. Lazaridis, Ravishankar K. Iyer. 157-189 [doi]
• Activation From Sparse 2D Cardiac MRIsNivetha Jayakumar, Jiarui Xing, Tonmoy Hossain, Frederick H. Epstein, Kenneth C. Bilchick, Miaomiao Zhang. 190-200 [doi]
• NoteContrast: Contrastive Language-Diagnostic Pretraining for Medical TextPrajwal Kailas, Max Homilius, Rahul C. Deo, Calum A. MacRae. 201-216 [doi]
• How Fair are Medical Imaging Foundation Models?Muhammad Osama Khan, Muhammad Muneeb Afzal, Shujaat Mirza, Yi Fang. 217-231 [doi]
• Learning Generalized Medical Image Representations Through Image-Graph Contrastive PretrainingSameer Tajdin Khanna, Daniel Michael, Marinka Zitnik, Pranav Rajpurkar. 232-243 [doi]
• Multimodal Pretraining of Medical Time Series and NotesRyan King, Tianbao Yang, Bobak J. Mortazavi. 244-255 [doi]
• Deep Multimodal Fusion for Surgical Feedback ClassificationRafal Kocielnik, Elyssa Y. Wong, Timothy N. Chu, Lydia Lin, De-An Huang, Jiayun Wang, Anima Anandkumar, Andrew J. Hung. 256-267 [doi]
• On the Importance of Step-wise Embeddings for Heterogeneous Clinical Time-SeriesRita Kuznetsova, Alizée Pace, Manuel Burger, Hugo Yèche, Gunnar Rätsch. 268-291 [doi]
• Gradient-Map-Guided Adaptive Domain Generalization for Cross Modality MRI SegmentationBingnan Li, Zhitong Gao, Xuming He 0001. 292-306 [doi]
• Anytime-valid inference in N-of-1 trialsIvana Malenica, Yongyi Guo, Kyra Gan, Stefan Konigorski. 307-322 [doi]
• Compositional Q-learning for electrolyte repletion with imbalanced patient sub-populationsAishwarya Mandyam, Andrew Jones, Jiayu Yao, Krzysztof Laudanski, Barbara E. Engelhardt. 323-339 [doi]
• Designing and evaluating an online reinforcement learning agent for physical exercise recommendations in N-of-1 trialsDominik Meier, Ipek Ensari, Stefan Konigorski. 340-352 [doi]
• Med-Flamingo: a Multimodal Medical Few-shot LearnerMichael Moor, Qian Huang, Shirley Wu, Michihiro Yasunaga, Yash Dalmia, Jure Leskovec, Cyril Zakka, Eduardo Pontes Reis, Pranav Rajpurkar. 353-367 [doi]
• Supervised Electrocardiogram(ECG) Features Outperform Knowledge-based And Unsupervised Features In Individualized Survival PredictionYousef Nademi, Sunil Vasu Kalmady, Weijie Sun 0004, Shiang Qi, Abram Hindle, Padma Kaul, Russell Greiner. 368-384 [doi]
• Pragmatic Radiology Report GenerationDang Nguyen, Chacha Chen, He He, Chenhao Tan. 385-402 [doi]
• Temporal Supervised Contrastive Learning for Modeling Patient Risk ProgressionShahriar Noroozizadeh, Jeremy C. Weiss, George H. Chen. 403-427 [doi]
• Nonparametric modeling of the composite effect of multiple nutrients on blood glucose dynamicsArina Odnoblyudova, Caglar Hizli, St John, Andrea Cognolato, Anne Juuti, Simo Särkkä, Kirsi Pietiläinen, Pekka Marttinen. 428-444 [doi]
• Using Reinforcement Learning for Multi-Objective Cluster-Level Optimization of Non-Pharmaceutical Interventions for Infectious DiseaseXueqiao Peng, Jiaqi Xu, Xi Chen, Dinh Song An Nguyen, Andrew Perrault. 445-460 [doi]
• Mixture of Coupled HMMs for Robust Modeling of Multivariate Healthcare Time SeriesOnur Poyraz, Pekka Marttinen. 461-479 [doi]
• Automated Cardiovascular Record Retrieval by Multimodal Learning between Electrocardiogram and Clinical ReportJielin Qiu, Jiacheng Zhu, Shiqi Liu, William Han, Jingqi Zhang, Chaojing Duan, Michael A. Rosenberg, Emerson Liu, Douglas Weber, Ding Zhao. 480-497 [doi]
• MULTIPAR: Supervised Irregular Tensor Factorization with Multi-task Learning for Computational PhenotypingYifei Ren, Jian Lou 0001, Li Xiong 0001, Joyce C. Ho, Xiaoqian Jiang, Sivasubramanium Venkatraman Bhavani. 498-511 [doi]
• Robust semi-supervised segmentation with timestep ensembling diffusion modelsMargherita Rosnati, Mélanie Roschewitz, Ben Glocker. 512-527 [doi]
• LymphoML: An interpretable artificial intelligence-based method identifies morphologic features that correlate with lymphoma subtypeVivek Shankar, Xiaoli Yang, Vrishab Krishna, Brent Tan, Oscar Silva, Rebecca Rojansky, Andrew Y. Ng, Fabiola Valvert, Edward Briercheck, David Weinstock, Yasodha Natkunam, Sebastian Fernandez-Pol, Pranav Rajpurkar. 528-558 [doi]
• Eigen: Expert-Informed Joint Learning Aggregation for High-Fidelity Information Extraction from Document ImagesAbhishek Singh, Venkatapathy Subramanian, Ayush Maheshwari, Pradeep Narayan, Devi Prasad Shetty, Ganesh Ramakrishnan. 559-573 [doi]
• Interpretable Survival Analysis for Heart Failure Risk PredictionMike Van Ness, Tomas M. Bosschieter, Natasha Din, Andrew Ambrosy, Alexander Sandhu, Madeleine Udell. 574-593 [doi]
• GANcMRI: Cardiac magnetic resonance video generation and physiologic guidance using latent space promptingMilos Vukadinovic, Alan C. Kwan, Debiao Li, David Ouyang. 594-606 [doi]
• Interpretable Mechanistic Representations for Meal-level Glycemic Control in the WildKe Alexander Wang, Emily B. Fox. 607-622 [doi]
• TransEHR: Self-Supervised Transformer for Clinical Time Series DataYanbo Xu, Shangqing Xu, Manav Ramprassad, Alexey Tumanov, Chao Zhang. 623-635 [doi]
• Dynamic Interpretable Change Point Detection for Physiological Data AnalysisJennifer Yu, Tina Behrouzi, Kopal Garg, Anna Goldenberg, Sana Tonekaboni. 636-649 [doi]
• Zero-Shot ECG Diagnosis with Large Language Models and Retrieval-Augmented GenerationHan Yu 0008, Peikun Guo, Akane Sano. 650-663 [doi]
• Diffusion Model-Based Data Augmentation for Lung Ultrasound Classification with Limited DataXiaohui Zhang, Ahana Gangopadhyay, Hsi-Ming Chang, Ravi Soni. 664-676 [doi]