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MLHC 2023: New York, NY, USA
- Kaivalya Deshpande, Madalina Fiterau, Shalmali Joshi, Zachary C. Lipton, Rajesh Ranganath, Iñigo Urteaga, Serene Yeung:
Machine Learning for Healthcare Conference, MLHC 2023, 11-12 August 2023, New York, USA. Proceedings of Machine Learning Research 219, PMLR 2023 - Griffin Adams, Jason Zuckerg, Noémie Elhadad:
A Meta-Evaluation of Faithfulness Metrics for Long-Form Hospital-Course Summarization. 2-30 - Célia Wafa Ayad, Thomas Bonnier, Benjamin Bosch, Jesse Read, Sonali Parbhoo:
Which Explanation Makes Sense? A Critical Evaluation of Local Explanations for Assessing Cervical Cancer Risk. 31-49 - Ali Behrouz, Margo I. Seltzer:
Anomaly Detection in Human Brain via Inductive Learning on Temporal Multiplex Networks. 50-75 - David Calhas, Rui Henriques:
EEG to fMRI Synthesis Benefits from Attentional Graphs of Electrode Relationships. 76-93 - Cheng Cheng, Jeremy C. Weiss:
Typed Markers and Context for Clinical Temporal Relation Extraction. 94-109 - Rhys Compton, Lily H. Zhang, Aahlad Manas Puli, Rajesh Ranganath:
When More is Less: Incorporating Additional Datasets Can Hurt Performance By Introducing Spurious Correlations. 110-127 - Hyungrok Do, Yuxin Chang, Yoon-Sang Cho, Padhraic Smyth, Judy Zhong:
When More is Less: Incorporating Additional Datasets Can Hurt Performance By Introducing Spurious Correlations. 128-149 - Ahmed Elhussein, Gamze Gürsoy:
Privacy-preserving patient clustering for personalized federated learnings. 150-166 - Hamed Fayyaz, Abigail Strang, Rahmatollah Beheshti:
Bringing At-home Pediatric Sleep Apnea Testing Closer to Reality: A Multi-modal Transformer Approach. 167-185 - Muhammad Hasan Ferdous, Uzma Hasan, Md. Osman Gani:
CDANs: Temporal Causal Discovery from Autocorrelated and Non-Stationary Time Series Data. 186-207 - David Elias Fresacher, Stefan Röhrl, Christian Klenk, Johanna Erber, Hedwig Irl, Dominik Heim, Manuel Lengl, Simon Schumann, Martin Knopp
, Martin Schlegel, Sebastian Rasch, Oliver Hayden, Klaus Diepold:
Composition Counts: A Machine Learning View on Immunothrombosis using Quantitative Phase Imaging. 208-229 - Faris F. Gulamali, Ashwin Sawant, Ira Hofer, Matthew A. Levin, Alexander Charney, Karandeep Singh, Benjamin S. Glicksberg, Girish N. Nadkarni:
Online Unsupervised Representation Learning of Waveforms in the Intensive Care Unit via a novel cooperative framework: Spatially Resolved Temporal Networks (SpaRTEn). 230-247 - Hao He, Yuan Yuan, Ying-Cong Chen, Peng Cao, Dina Katabi:
Contactless Oxygen Monitoring with Radio Waves and Gated Transformer. 248-265 - Danliang Ho, Mehul Motani:
Multi-view Modelling of Longitudinal Health Data for Improved Prognostication of Colorectal Cancer Recurrence. 265-284 - Zhe Huang, Benjamin S. Wessler, Michael C. Hughes:
Detecting Heart Disease from Multi-View Ultrasound Images via Supervised Attention Multiple Instance Learning. 285-307 - Yamac Alican Isik, Paidamoyo Chapfuwa, Connor Davis, Ricardo Henao:
Hawkes Process with Flexible Triggering Kernels. 308-320 - Hyewon Jeong, Collin M. Stultz, Marzyeh Ghassemi:
Deep Metric Learning for the Hemodynamics Inference with Electrocardiogram Signals. 321-342 - Sharon Jiang, Shannon Shen, Monica Agrawal, Barbara D. Lam, Nicholas Kurtzman, Steven Horng, David R. Karger, David A. Sontag:
Conceptualizing Machine Learning for Dynamic Information Retrieval of Electronic Health Record Notes. 343-359 - Mert Ketenci, Shreyas Bhave, Noemie Elhadad, Adler J. Perotte:
Maximum Likelihood Estimation of Flexible Survival Densities with Importance Sampling. 360-380 - Sameer Tajdin Khanna, Adam Dejl, Kibo Yoon, Steven QH Truong, Hanh Duong, Agustina Saenz, Pranav Rajpurkar:
RadGraph2: Modeling Disease Progression in Radiology Reports via Hierarchical Information Extraction. 381-402 - Alex Labach, Aslesha Pokhrel, Xiao Shi Huang, Saba Zuberi, Seung Eun Yi, Maksims Volkovs, Tomi Poutanen, Rahul G. Krishnan:
DuETT: Dual Event Time Transformer for Electronic Health Records. 403-422 - Kwanhyung Lee, Soojeong Lee, Sangchul Hahn, Heejung Hyun, Edward Choi, Byungeun Ahn, Joohyung Lee:
Learning Missing Modal Electronic Health Records with Unified Multi-modal Data Embedding and Modality-Aware Attention. 423-442 - Rajiv Movva, Divya Shanmugam, Kaihua Hou, Priya Pathak, John V. Guttag, Nikhil Garg, Emma Pierson:
Coarse race data conceals disparities in clinical risk score performance. 443-472 - Makiya Nakashima, Donna Salem, HW Wilson Tang, Christopher Nguyen, Tae-Hyun Hwang, Ding Zhao, Byung-Hak Kim, Deborah Kwon, David Chen:
Reducing Contextual Bias in Cardiac Magnetic Resonance Imaging Deep Learning Using Contrastive Self-Supervision. 473-488 - Ahmed Ammar Naseer, Benjamin Walker, Christopher Landon, Andrew Ambrosy, Marat Fudim, Nicholas Wysham, Botros Toro, Sumanth Swaminathan, Terry J. Lyons:
ScoEHR: Generating Synthetic Electronic Health Records using Continuous-time Diffusion Models. 489-508 - Alexis Nolin-Lapalme, Robert Avram, Hussin Julie:
PrivECG: generating private ECG for end-to-end anonymization. 509-528 - Erkin Ötles, Brian T. Denton, Jenna Wiens:
Updating Clinical Risk Stratification Models Using Rank-Based Compatibility: Approaches for Evaluating and Optimizing Clinician-Model Team Performance. 529-547 - Anil Palepu, Andrew Beam:
TIER: Text-Image Entropy Regularization for Medical CLIP-style models. 548-564 - Jay B. Patel, Syed Rakin Ahmed, Ken Chang, Praveer Singh, Mishka Gidwani, Katharina Hoebel, Albert E. Kim, Christopher P. Bridge, Chung-Jen Teng, Xiaomei Li, Gongwen Xu, Megan McDonald, Ayal Aizer, Wenya Linda Bi, K. Ina Ly, Bruce Rosen, Priscilla K. Brastianos, Raymond Y. Huang, Elizabeth R. Gerstner, Jayashree Kalpathy-Cramer:
A Deep Learning Based Framework for Joint Image Registration and Segmentation of Brain Metastases on Magnetic Resonance Imaging. 565-587 - Melanie F. Pradier, Niranjani Prasad, Paidamoyo Chapfuwa, Sahra Ghalebikesabi, Maximilian Ilse, Steven Woodhouse, Rebecca Elyanow, Javier Zazo, Javier González Hernández, Julia Greissl, Edward Meeds:
AIRIVA: A Deep Generative Model of Adaptive Immune Repertoires. 588-611 - Eric W. Prince
EASL: A Framework for Designing, Implementing, and Evaluating ML Solutions in Clinical Healthcare Settings. 612-630 - Sanjana Ramprasad, Elisa Ferracane, Sai P. Selvaraj:
Generating more faithful and consistent SOAP notes using attribute-specific parameters. 631-649 - Mercy Prasanna Ranjit, Gopinath Ganapathy, Ranjit Manuel, Tanuja Ganu:
Retrieval Augmented Chest X-Ray Report Generation using OpenAI GPT models. 650-666 - Xiaobin Shen, Jonathan Elmer, George H. Chen:
Neurological Prognostication of Post-Cardiac-Arrest Coma Patients Using EEG Data: A Dynamic Survival Analysis Framework with Competing Risks. 667-690 - Pranav Singh, Jacopo Cirrone:
Efficient Representation Learning for Healthcare with Cross-Architectural Self-Supervision. 691-711 - Ömer Sümer, Rebekah L. Waikel, Suzanna E. Ledgister Hanchard, Dat Duong, Peter Krawitz, Cristina Conati, Benjamin D. Solomon, Elisabeth André:
Region-based Saliency Explanations on the Recognition of Facial Genetic Syndromes. 712-736 - Pranav Vaid, Serena Yeung, Anita Rau:
Robust Semi-supervised Detection of Hands in Diverse Open Surgery Environments. 736-753 - Somin Wadhwa, Jay DeYoung, Benjamin E. Nye, Silvio Amir, Byron C. Wallace:
Jointly Extracting Interventions, Outcomes, and Findings from RCT Reports with LLMs. 754-771 - Mengqian Wang, Ilya Valmianski, Xavier Amatriain, Anitha Kannan:
Learning functional sections in medical conversations: iterative pseudo-labeling and human-in-the-loop approach. 772-787 - Peiqi Wang, Yingcheng Liu, Ching-Yun Ko, William M. Wells III, Seth J. Berkowitz, Steven Horng, Polina Golland:
Sample-Specific Debiasing for Better Image-Text Models. 788-803 - Yuqing Wang, Yun Zhao, Linda R. Petzold:
Are Large Language Models Ready for Healthcare? A Comparative Study on Clinical Language Understanding. 804-823 - Sophie Wharrie, Zhiyu Yang, Andrea Ganna, Samuel Kaski:
Characterizing personalized effects of family information on disease risk using graph representation learning. 824-845 - Cliff Wong, Sheng Zhang, Yu Gu, Christine Moung, Jacob Abel, Naoto Usuyama, Roshanthi Weerasinghe, Brian Piening, Tristan Naumann, Carlo Bifulco, Hoifung Poon:
Scaling Clinical Trial Matching Using Large Language Models: A Case Study in Oncology. 846-862 - Yu Wu, Dimitris Spathis, Hong Jia, Ignacio Perez-Pozuelo, Tomas I. Gonzales, Søren Brage, Nicholas J. Wareham, Cecilia Mascolo:
UDAMA: Unsupervised Domain Adaptation through Multi-discriminator Adversarial Training with Noisy Labels Improves Cardio-fitness Prediction. 863-883 - Hongjing Xia, Joshua C. Chang, Sarah Nowak, Sonya Mahajan, Rohit Mahajan, Ted L. Chang, Carson C. Chow:
Interpretable (not just posthoc-explainable) heterogeneous survivors bias-corrected treatment effects for assignment of postdischarge interventions to prevent readmissions. 884-905 - Jiaai Xu, Rada Mihalcea, Elena Frank, Srijan Sen, Maggie Makar:
Uncovering the Varied Impact of Behavioral Change Messages on Population Groups. 906-922 - Lida Zhang, Bobak J. Mortazavi:
Semi-supervised Meta-learning for Multi-source Heterogeneity in Time-series Data. 923-941 - Jian Zhu, Ilya Valmianski, Anitha Kannan:
Dialogue-Contextualized Re-ranking for Medical History-Taking. 942-958
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