ML4H@NeurIPS

Keyphrases

Publications

2023

Ke Alexander Wang, Emily B. Fox
Interpretable Mechanistic Representations for Meal-level Glycemic Control in the Wild. ML4H@NeurIPS (2023)
Nivetha Jayakumar, Jiarui Xing, Tonmoy Hossain, Frederick H. Epstein, Kenneth C. Bilchick, Miaomiao Zhang
Activation From Sparse 2D Cardiac MRIs. ML4H@NeurIPS (2023)
Yanbo Xu, Shangqing Xu, Manav Ramprassad, Alexey Tumanov, Chao Zhang
TransEHR: Self-Supervised Transformer for Clinical Time Series Data. ML4H@NeurIPS (2023)
Prajwal Kailas, Max Homilius, Rahul C. Deo, Calum A. MacRae
NoteContrast: Contrastive Language-Diagnostic Pretraining for Medical Text. ML4H@NeurIPS (2023)
Dang Nguyen, Chacha Chen, He He, Chenhao Tan
Pragmatic Radiology Report Generation. ML4H@NeurIPS (2023)
Ryan King, Tianbao Yang, Bobak J. Mortazavi
Multimodal Pretraining of Medical Time Series and Notes. ML4H@NeurIPS (2023)
Manuel Burger, Gunnar Rätsch, Rita Kuznetsova
Multi-modal Graph Learning over UMLS Knowledge Graphs. ML4H@NeurIPS (2023)
Arina Odnoblyudova, Caglar Hizli, ST John, Andrea Cognolato, Anne Juuti, Simo Särkkä, Kirsi Pietiläinen, Pekka Marttinen
Nonparametric modeling of the composite effect of multiple nutrients on blood glucose dynamics. ML4H@NeurIPS (2023)
Ethan Harvey, Wansu Chen, David M. Kent, Michael C. Hughes
A Probabilistic Method to Predict Classifier Accuracy on Larger Datasets given Small Pilot Data. ML4H@NeurIPS (2023)
Mike Van Ness, Tomas M. Bosschieter, Natasha Din, Andrew Ambrosy, Alexander Sandhu, Madeleine Udell
Interpretable Survival Analysis for Heart Failure Risk Prediction. ML4H@NeurIPS (2023)
Muhammad Osama Khan, Muhammad Muneeb Afzal, Shujaat Mirza, Yi Fang
How Fair are Medical Imaging Foundation Models? ML4H@NeurIPS (2023)
Onur Poyraz, Pekka Marttinen
Mixture of Coupled HMMs for Robust Modeling of Multivariate Healthcare Time Series. ML4H@NeurIPS (2023)
Abhishek Singh, Venkatapathy Subramanian, Ayush Maheshwari, Pradeep Narayan, Devi Prasad Shetty, Ganesh Ramakrishnan
Eigen: Expert-Informed Joint Learning Aggregation for High-Fidelity Information Extraction from Document Images. ML4H@NeurIPS (2023)
Han Yu, Peikun Guo, Akane Sano
Zero-Shot ECG Diagnosis with Large Language Models and Retrieval-Augmented Generation. ML4H@NeurIPS (2023)
Ali Behrouz, Farnoosh Hashemi
Learning Temporal Higher-order Patterns to Detect Anomalous Brain Activity. ML4H@NeurIPS (2023)
Yifei Ren, Jian Lou, Li Xiong, Joyce C. Ho, Xiaoqian Jiang, Sivasubramanium Venkatraman Bhavani
MULTIPAR: Supervised Irregular Tensor Factorization with Multi-task Learning for Computational Phenotyping. ML4H@NeurIPS (2023)
Dominik Meier, Ipek Ensari, Stefan Konigorski
Designing and evaluating an online reinforcement learning agent for physical exercise recommendations in N-of-1 trials. ML4H@NeurIPS (2023)
Milos Vukadinovic, Alan C. Kwan, Debiao Li, David Ouyang
GANcMRI: Cardiac magnetic resonance video generation and physiologic guidance using latent space prompting. ML4H@NeurIPS (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
Machine Learning for Health (ML4H) 2023. ML4H@NeurIPS (2023)
Vivek 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
LymphoML: An interpretable artificial intelligence-based method identifies morphologic features that correlate with lymphoma subtype. ML4H@NeurIPS (2023)
Fabian Gröger, Simone Lionetti, Philippe Gottfrois, Álvaro González-Jiménez, Matthew Groh, Roxana Daneshjou, Labelling Consortium, Alexander A. Navarini, Marc Pouly
Towards Reliable Dermatology Evaluation Benchmarks. ML4H@NeurIPS (2023)
Bingnan Li, Zhitong Gao, Xuming He
Gradient-Map-Guided Adaptive Domain Generalization for Cross Modality MRI Segmentation. ML4H@NeurIPS (2023)
Chang Hu, Krishnakant V. Saboo, Ahmad H. Ali, Brian D. Juran, Konstantinos N. Lazaridis, Ravishankar K. Iyer
REMEDI: REinforcement learning-driven adaptive MEtabolism modeling of primary sclerosing cholangitis DIsease progression. ML4H@NeurIPS (2023)
Jennifer Yu, Tina Behrouzi, Kopal Garg, Anna Goldenberg, Sana Tonekaboni
Dynamic Interpretable Change Point Detection for Physiological Data Analysis. ML4H@NeurIPS (2023)
Yousef Nademi, Sunil Vasu Kalmady, Weijie Sun, Shiang Qi, Abram Hindle, Padma Kaul, Russell Greiner
Supervised Electrocardiogram(ECG) Features Outperform Knowledge-based And Unsupervised Features In Individualized Survival Prediction. ML4H@NeurIPS (2023)
Rafal Kocielnik, Elyssa Y. Wong, Timothy N. Chu, Lydia Lin, De-An Huang, Jiayun Wang, Anima Anandkumar, Andrew J. Hung
Deep Multimodal Fusion for Surgical Feedback Classification. ML4H@NeurIPS (2023)
Margherita Rosnati, Mélanie Roschewitz, Ben Glocker
Robust semi-supervised segmentation with timestep ensembling diffusion models. ML4H@NeurIPS (2023)
Xueqiao Peng, Jiaqi Xu, Xi Chen, Dinh Song An Nguyen, Andrew Perrault
Using Reinforcement Learning for Multi-Objective Cluster-Level Optimization of Non-Pharmaceutical Interventions for Infectious Disease. ML4H@NeurIPS (2023)
Rita Kuznetsova, Alizée Pace, Manuel Burger, Hugo Yèche, Gunnar Rätsch
On the Importance of Step-wise Embeddings for Heterogeneous Clinical Time-Series. ML4H@NeurIPS (2023)
Michael Moor, Qian Huang, Shirley Wu, Michihiro Yasunaga, Yash Dalmia, Jure Leskovec, Cyril Zakka, Eduardo Pontes Reis, Pranav Rajpurkar
Med-Flamingo: a Multimodal Medical Few-shot Learner. ML4H@NeurIPS (2023)
Shobhit Agarwal, Yevgeniy R. Semenov, William Lotter
Representing visual classification as a linear combination of words. ML4H@NeurIPS (2023)
Shahriar Noroozizadeh, Jeremy C. Weiss, George H. Chen
Temporal Supervised Contrastive Learning for Modeling Patient Risk Progression. ML4H@NeurIPS (2023)
Mohammad Reza Hosseinzadeh Taher, Masaki Ikuta, Ravi Soni
Curriculum Self-Supervised Learning for 3D CT Cardiac Image Segmentation. ML4H@NeurIPS (2023)
Jielin Qiu, Jiacheng Zhu, Shiqi Liu, William Han, Jingqi Zhang, Chaojing Duan, Michael A. Rosenberg, Emerson Liu, Douglas Weber, Ding Zhao
Automated Cardiovascular Record Retrieval by Multimodal Learning between Electrocardiogram and Clinical Report. ML4H@NeurIPS (2023)
Muhammad Muneeb Afzal, Muhammad Osama Khan, Shujaat Mirza
Towards Equitable Kidney Tumor Segmentation: Bias Evaluation and Mitigation. ML4H@NeurIPS (2023)
Sameer Tajdin Khanna, Daniel Michael, Marinka Zitnik, Pranav Rajpurkar
Learning Generalized Medical Image Representations Through Image-Graph Contrastive Pretraining. ML4H@NeurIPS (2023)
Aishwarya Mandyam, Andrew Jones, Jiayu Yao, Krzysztof Laudanski, Barbara E. Engelhardt
Compositional Q-learning for electrolyte repletion with imbalanced patient sub-populations. ML4H@NeurIPS (2023)
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
LLMs Accelerate Annotation for Medical Information Extraction. ML4H@NeurIPS (2023)
Xiaohui Zhang, Ahana Gangopadhyay, Hsi-Ming Chang, Ravi Soni
Diffusion Model-Based Data Augmentation for Lung Ultrasound Classification with Limited Data. ML4H@NeurIPS (2023)
Ivana Malenica, Yongyi Guo, Kyra Gan, Stefan Konigorski
Anytime-valid inference in N-of-1 trials. ML4H@NeurIPS (2023)

volume 225, 2023

Machine Learning for Health, ML4H@NeurIPS 2023, 10 December 2023, New Orleans, Louisiana, USA. ML4H@NeurIPS 225 (2023)

2022

volume 193, 2022

Machine Learning for Health, ML4H 2022, 28 November 2022, New Orleans, Lousiana, USA & Virtual. ML4H@NeurIPS 193 (2022)