Posters A:
ID 01: Interpretable (not just posthoc-explainable) heterogeneous survivor bias-corrected treatment effects for assignment of postdischarge interventions to prevent readmissions
Hongjing Xia, Joshua C Chang, Sarah Nowak, Ted Chang, Sonya Mahajan, Rohit Mahajan, Carson C Chow
ID 08: Sample-Specific Debiasing for Better Image-Text Models
Peiqi Wang, Yingcheng Liu, Ching-Yun Ko, William M Wells, Seth Berkowitz, Steven Horng, Polina Golland
ID 13: Coarse race data conceals disparities in clinical risk score performance
Rajiv Movva, Divya Shanmugam, Kaihua Hou, Priya Pathak, John Guttag, Nikhil Garg, Emma Pierson
ID 23: Typed Markers and Context for Clinical Temporal Relation Extraction
Cheng Cheng, Jeremy C Weiss
ID 28: Characterizing personalized effects of family information on disease risk using graph representation learning
Sophie Wharrie, Zhiyu Yang, Andrea Ganna, Samuel Kaski
ID 29: Online Unsupervised Representation Learning of Waveforms in the Intensive Care Unit via a novel cooperative framework: Spatially Resolved Temporal Networks (SpaRTEn)
Faris F Gulamali, Ashwin Sawant, Ira Hofer, Matthew Levin, Alexander Charney, Karandeep Singh, Benjamin Glicksberg, Girish Nadkarni
ID 34: Are Large Language Models Ready for Healthcare? A Comparative Study on Clinical Language Understanding
Yuqing Wang, Yun Zhao, Linda R Petzold
ID 38: Privacy-preserving patient clustering for personalized federated learning
Ahmed Elhussein, Gamze Gursoy
ID 39: EEG to fMRI Synthesis Benefits from Attentional Graphs of Electrode Relationships
David Calhas, Rui Henriques
ID 49: Detecting Heart Disease from Multi-View Ultrasound Images via Supervised Attention Multiple Instance Learning
Zhe Huang, Benjamin Wessler, Michael C Hughes
ID 53: Dialogue-Contextualized Re-ranking for Medical History-Taking
Jian Zhu, Ilya Valmianski, Anitha Kannan
ID 57: Learning functional sections in medical conversations: iterative pseudo-labeling and human-in-the-loop approach
Mengqian Wang, Ilya Valmianski, Xavier Amatriain, Anitha Kannan
ID 64: Reducing Contextual Bias in Cardiac Magnetic Resonance Imaging Deep Learning Using Contrastive Self-Supervision
Makiya Nakashima, Donna Salam, Richard Grimm, W.H. Wilson Tang, Christopher Nguyen, Tae Hyun Hwang, Ding Zhao, Byung-Hak Kim, Deborah Kwon, David Chen
ID 66: Multi-view Modelling of Longitudinal Health Data for Improved Prognostication of Colorectal Cancer Recurrence
Danliang Ho, Mehul Motani
ID 67: Retrieval Augmented Chest X-Ray Report Generation using Open AI GPT models
Mercy P Ranjit
ID 69: Composition Counts: A Machine Learning View on Immunothrombosis using Quantitative Phase Imaging
David Fresacher, Stefan Röhrl, Christian Klenk, Johanna Erber, Hedwig Irl, Manuel Lengl, Simon Schumann, Dominik Heim, Martin Knopp, Martin Schlegel, Sebastian Rasch, Oliver Hayden, Klaus Diepold
ID 73: AIRIVA: A Deep Generative Model of Adaptive Immune Repertoires
Melanie Fernandez Pradier, Niranjani Prasad, Paidamoyo Chapfuwa, Sahra Ghalebikesabi, Max Ilse, Steven Woodhouse, Rebecca Elyanow, Javier Zazo, Javier Gonzalez, Julia Greissl, Ted Meeds
ID 93: A Hierarchical Training Paradigm for Antibody Structure-sequence Co-design
Fang Wu, Siyuan Li, Buyong Ma, Stan Z. Li
ID 97: Region-based Saliency Explanations on the Recognition of Facial Genetic Syndromes
Ömer Sümer, Rebekah L. Waikel, Suzanna E. Ledgister Hanchard, Dat B Duong, Peter Krawitz, Cristina Conati, Benjamin D. Solomon, Elisabeth André
ID 103: Updating Clinical Risk Stratification Models Using Rank-Based Compatibility: Approaches for Evaluating and Optimizing Joint Clinician-Model Team Performance
Erkin Otles, Brian Denton, Jenna Wiens
ID 110: Uncovering the Varied Impact of Behavioral Change Messages on Population Groups]{Uncovering the Varied Impact of Behavioral Change Messages on Population Groups
Jiaai Xu, Rada Mihalcea, Elena Frank, Srijan Sen, Maggie Makar
ID 116: Hawkes Process with Flexible Triggering Kernels
Yamac A Isik, Paidamoyo Chapfuwa, Connor Davis, Ricardo Henao
ID 119: Fair Survival Time Prediction via Mutual Information Minimization
Hyungrok Do, Yuxin Chang, Yoon Sang Cho, Padhraic Smyth, Judy Zhong
ID 124: Jointly Extracting Interventions, Outcomes, and Findings from RCT Reports with LLMs
Somin Wadhwa, Jay DeYoung, Benjamin Nye, Silvio Amir, Byron Wallace
Posters B:
ID 125: Efficient Representation Learning for Healthcare with Cross-Architectural Self-Supervision
Pranav Singh, Jacopo Cirrone
ID 128: TIER: Text-Image Entropy Regularization for Medical CLIP-style models
Anil Palepu, Andrew Beam
ID 136: UDAMA: Unsupervised Domain Adaptation through Multi-discriminator Adversarial Training with Noisy Labels Improves Cardio-fitness Prediction
Yu Wu, Dimitris Spathis, Hong Jia, Ignacio Perez-Pozuelo, Tomas Gonzales, Soren Brage, Nicholas J. Wareham, Cecilia Mascolo
ID 138: Maximum Likelihood Estimation of Flexible Survival Densities with Importance Sampling
Mert Ketenci, Shreyas Bhave, Noémie Elhadad, Adler Perotte
ID 140: A Deep Learning Based Framework for Joint Image Registration and Segmentation of Brain Metastases on Magnetic Resonance Imaging
Jay Patel, Syed Rakin Ahmed, Ken Chang, Praveer Singh, Mishka Gidwani, Katharina Hoebel, Albert Kim, Christopher P Bridge, Chung-Jen Teng, Xiaomei Li, Gongwen Xu, Megan McDonald, Ayal Aizer, Wenya Linda Bi, K. Ina Ly, Bruce Rosen, Priscilla Brastianos, Raymond Huang, Elizabeth Gerstner, Jayashree Kalpathy-Cramer
ID 145: ScoEHR: Generating Synthetic Electronic Health Records using Continuous-time Diffusion Models
Ahmed A Naseer, Benjamin Walker, Christopher Landon, Andrew Ambrosy, Marat Fudim, Nicholas Wysham, Botros Toro, Sumanth Swaminathan, Terry J Lyons
ID 147: Conceptualizing Machine Learning for Dynamic Information Retrieval of Electronic Health Record Notes
Sharon Jiang, Zejiang Shen, Monica Agrawal, Barbara Lam, Nicholas Kurtzman, Steven Horng, David Karger, David Sontag
ID 150: A Meta-Evaluation of Faithfulness Metrics for Long-Form Hospital-Course Summarization
Griffin T Adams, Jason Zucker, Noemie Elhadad
ID 153: Semi-supervised Meta-learning for Multi-source Heterogeneity in Time-series Data
Lida Zhang, Bobak J Mortazavi
ID 155: Deep Metric Learning for the Hemodynamics Inference with Electrocardiogram Signals
Hyewon Jeong, Collin Stultz, Marzyeh Ghassemi
ID 156: EASL: A Framework for Designing, Implementing, and Evaluating ML Solutions in Clinical Healthcare Settings
Eric Prince, Todd Hankinson, Carsten Görg
ID 160: Anomaly Detection in Human Brain via Inductive Learning on Temporal Multiplex Networks
Ali Behrouz, Margo Seltzer
ID 162: Contactless Oxygen Monitoring with Radio Waves and Gated Transformer
Hao He, Yuan Yuan, Yingcong Chen, Peng Cao, Dina Katabi
ID 166: DuETT: Dual Event Time Transformer for Electronic Health Records
Alex Labach, Aslesha Pokhrel, Xiao Shi Huang, Saba Zuberi, Seung Eun Yi, Maksims N Volkovs, Tomi Poutanen, Rahul G. Krishnan
ID 175: Neurological Prognostication of Post-Cardiac-Arrest Coma Patients Using EEG Data: A Dynamic Survival Analysis Framework with Competing Risks
Xiaobin Shen, Jonathan Elmer, George H Chen
ID 177: PrivECG: generating private ECG for end-to-end anonymization
Alexis Nolin-Lapalme, Robert Avram, Julie Hussin
ID 181: RadGraph2: Introducing Hierarchical Characterisation of Changes from Priors in Radiology Report Graphs
Sameer T Khanna, Adam Dejl, Kibo Yoon, Quoc Hung Truong, Hanh Duong, Agustina Saenz, Pranav Rajpurkar
ID 189: When More is Less: Incorporating Additional Datasets Can Hurt Performance By Introducing Spurious Correlations
Rhys Compton, Lily Zhang, Aahlad Puli, Rajesh Ranganath
ID 191: CDANs: Temporal Causal Discovery from Autocorrelated and Non-Stationary Time Series Data
Muhammad Hasan Ferdous, Uzma Hasan, Md Osman Gani
ID 196: Robust Semi-supervised Detection of Hands in Diverse Open Surgery Environments
Pranav K Vaid (Stanford University)*; Serena Yeung (Stanford University); Anita Rau
ID 197: Generating more faithful and consistent SOAP notes
Sanjana Ramprasad, Elisa Ferracane, Sai Prabhakar Pandi Selvaraj
ID 199: Scaling Clinical Trial Matching Using Large Language Models: A Case Study in Oncology
Cliff R Wong, Sheng Zhang, Yu Gu, Christine Moung, Jacob Abel, Naoto Usuyama, Roshanthi Weerasinghe, Brian Piening, Tristan Naumann, Carlo Bifulco, Hoifung Poon
ID 201: Learning Missing Modal Electronic Health Records with Unified Multi-modal Data Embedding and Modality-Aware Attention
Kwanhyung Lee, Joohyung Lee, Sangchul Hahn, Heejung Hyun, Byung Eun Ahn, Edward Choi, SooJeong Lee
ID 203: Bringing At-home Pediatric Sleep Apnea Testing Closer to Reality: A Multi-modal Transformer Approach
Hamed Fayyaz, Abigail Straing, Rahmatollah Beheshti
ID 204: Which Explanation Makes Sense? A Critical Evaluation of Local Explanations for Assessing Cervical Cancer Risk Factors
Wafa Celia Ayad, Thomas Bonnier, Benjamin Bosch, Jesse Read, Sonali Parbhoo
Posters C (Clinical Abstracts):
ID 9: Use of machine learning techniques for phenotyping ischemic stroke instead of the rule-based methods: A nationwide population-based study
Hyunsun LIm, Kwon-Duk Seo
ID 14: Identifying Time Trajectories in Risk Factors Documented in Clinical Notes and Predicting Hospitalizations and Emergency Department Visits during Home Health Care
Jiyoun Song, Se Hee Min, Sena Chae, Kathryn Bowles, Margaret McDonald, Mollie Hobensack, Yolanda Barron, Sridevi Sridharan, Anahita Davoudi, Sungho Oh, Lauren Evans, Maxim Topaz
ID 27: Early Identification of the Need for CRRT in Critically Ill Children: A Machine Learning Approach
Mark Wainwright, Qingyang Li, Shina Menon, Alexander Doud, David Van De Sompele, Kon Vong, Vijay Makkakode, Hillary Bourdrez
ID 30: Development of a dataset and prospective evaluation of a model to identify high quality papers on the clinical impact of pharmacist interventions
Maxime Thibault, Cynthia Tanguay
ID 52: Do social determinants of health documented in clinical notes improve hospital prediction in home healthcare?
Mollie Hobensack, Ana Davoudi, Maxim Topaz
ID 56: Natural language processing for stroke diagnostic imaging characterization
Brian Bursic, Andrew Wenhao Cao, Jinyue Feng, Amy Y.X. Yu, Moira Kapral, Frank Rudzicz, Fahad Razak, Amol Verma
ID 58: Developing a Patient Similarity Network for Predicting Post-stroke Urinary Tract Infection Risk in Hospitalized Immobile Patients
Zidu Xu, Yaowen Gu, Chen Zhu, Maxim Topaz
ID 72: Evaluating the Quality of Salvaged Blood Products Using Stimulated Raman Spectroscopy and Deep Learning
Daniel A Alber, David Kurland, Andrew Smith, Karl Sangwon, Ilene Tisnovsky, Nora Kim, Alex Eremiev, Emily Lock, Eric Oermann, Daniel Orringer, Darryl Lau
ID 74: Faster R-CNN Detection of Fractures in Pediatric Upper Extremity Radiographs
John Zech, Tony Wong
ID 76: Improving the Quality of NEWS by Learning from the Past
Allan Pang, Alwyn Kotze, Geoff Hall, Owen Johnson, Marc De Kamps
ID 79: Examining The Ability of Different ML Approaches to Predict Health Outcomes with Digital Health Platform
Abhimanyu Kumbara
ID 86: A Counterfactual-based Approach for Interpreting Deep Learning Models in Electrocardiogram Analysis
Hak Seung Lee, Yeji Lee, Jong-Hwan Jang, Yong-Yeon Jo, Min Sung Lee, Joon-myoung Kwon
ID 88: Natural Language Processing for Automated Extraction of Breast Cancer Information for the Cancer Registry
Adhari Dr AlZaabi, Abdulrahman AAlAbdulsalam
ID 91: Expanding Composite Disease Labels Improves ECG Deep Learning Model Performance for Structural Heart Disease Detection
Pierre Elias, Linyuan Jing, Joshua Finer, Dustin Hartzel, Chris Kelsey, Daniel Rocha, Jeffrey Ruhl, Christopher Haggerty, Timothy Poterucha
ID 105: Using Natural Language Processing on drug indications to predict working sources of infection
Chang Ho Yoon, Kevin Yuan, Qingze Gu, Ann Sarah Walker, David Eyre, Tingting Zhu, Henry Munby
ID 107: Towards Deploying Predictive Models for Maternal Health
Kaivalya Deshpande, Willie Boag, Freya Gulamali, Megan E Richards, Michael Gao, Namita Kansal, Vaishakhi Mayya, Mark Sendak, Ashraf Habib, Terrence Allen, Sarah McWay Boling, Melissa Bauer, Jennifer Gilner, Brenna Hughes, Courtney Mitchell, Heather Tally, Amanda Craig, Suresh Balu, William Knechtle
ID 108: Guidance Tool for Development and Implementation of Safe Healthcare AI
Anthony Li
ID 114: Enhancing Deep Learning in Detecting Acute Myocardial Infarction via Anatomically Informed 12-Lead ECG
Jessica Zegre-Hemsey, Cheng Ding, Brian Liu, David Wright, Salah Al-Zaiti, Xiao Hu, Ran Xiao
ID 117: Review of chronic obstructive pulmonacy disease operational definition model using machine learning model
Jung Hwa hong
ID 118: Leveraging data science for optimal follow-up of multimorbidity patients - a research protocol
Bernardo Neves, José Maria S Moreira
ID 123: Predicting Behavioral Emergencies in the Hospital
William Ratliff, Cara O'Brien, Mark Sendak, Linda Tang, Shems Saleh, Michael Gao, Suresh Balu, Marshall Nichols, Matt Gardner, Catie Dunn, Dustin Tart, Kelly Kester, Kristen Shirey
ID 133: Development of a Machine Learning Classification Model for ICU Admission Following Resuscitation at a Level I Trauma Center
Daniel Spalinski, Ali Memon, Daniel Nguyen, Sherif Zineldine, Hahn Soe-Lin, Jordan Weinberg
ID 142: A NLP pipeline to automatically predict human behavioral responses to viral epidemics like Ebola
Elie Donath, Nicholas Cheney, Laurent Hébert-Dufresne
ID 159: A machine learning model using in-game data for predicting unhealthy substance use among adolescents
Kammarauche Aneni, Ching-Hua Chen, Gaoqianxue Liu, Saatvik Kher, Lynn Fiellin
ID 165: Antihypertensive drug repurposing for dementia prevention: target trial emulations in two large-scale electronic health record systems
Deborah Blacker, Marie-Laure Charpignon, Bella Vakulenko-Lagun, Colin Magdamo, Bowen Su, Sudeshna Das, Anthony Philippakis, Munther Dahleh, Ioanna Tzoulaki, Mark Albers
ID 167: Not So Black and White: Confounders Mediate AI Prediction Of Race On Chest X-Rays
Preetham Bachina, Sean Garin, Pranav Kulkarni, Adway Kanhere, Daniel Kargilis, Vishwa S Parekh, Paul Yi
ID 171: A case study on deep learning label leakage identified during a silent trial
Linda Y Tang, Michael Gao, William Ratliff, Shems Saleh, Suresh Balu, Marshall Nichols, Mike Revoir, Emily Sterrett, Mark Sendak
ID 186: WhatGPT? Assessing Medical Student Use of Language Models During Clinical Clerkships
Rafael Schulman, Ali Razavi, Jonathan Chung, Jason Grullon