Posters A:

ID 05: Contrastive Learning of Medical Visual Representations from Paired Images and Text
Zhang, Yuhao; Jiang, Hang; Miura, Yasuhide; Manning, Christopher D; Langlotz, Curtis

ID 15: Unified Auto Clinical Scoring (Uni-ACS) with Interpretable ML models
Li, Anthony; Ong, Ming Lun; Oei, Chien Wei; Lian, Weixiang; Phua, Hwee Pin; Htet, Lin Htun; Lim, Wei Yen; Motani, Mehul

ID 20: Deep Cascade Learning for Optimal Medical Image Feature Representation
Wang, Junwen; Du, Xin; Farrahi, Katayoun; Niranjan, Mahesan

ID 24: Survival Seq2Seq: A Survival Model based on Sequence to Sequence Architecture
Pourjafari, Ebrahim; Ziaei, Navid; Rezaei, Mohammad R.; Sameizadeh, Amir; Shafiee, Mohammad; Alavinia, Mohammad; Abolghasemian, Mansour; Sajadi, Nick

ID 28: Density-Aware Personalized Training for Risk Prediction in Imbalanced Medical Data
Huo, Zepeng; Qian, Xiaoning ; Huang, Shuai; Wang, Zhangyang; Mortazavi, Bobak J

ID 32: Ensembling Neural Networks for Improved Prediction and Privacy in Early Diagnosis of Sepsis
Schamoni, Shigehiko; Hagmann, Michael; Riezler, Stefan

ID 34: Learning Optimal Dynamic Treatment Regimes Using Causal Tree Methods in Medicine
Persson, Joel; Feuerriegel, Stefan; Blümlein, Theresa

ID 36: GeoECG: Data Augmentation via Wasserstein Geodesic Perturbation for Robust Electrocardiogram Prediction
Zhu, Jiacheng; Qiu, Jielin; Yang, Zhuolin; Weber, Douglas J; Rosenberg, Michael; Liu, Emerson; Li, Bo; ZHAO, DING

ID 37: HiCu: Leveraging Hierarchy for Curriculum Learning in Automated ICD Coding
Ren, Weiming; Zeng, Ruijing; Wu, Tongzi; Zhu, Tianshu; Krishnan, Rahul G.

ID 38: Survival Mixture Density Networks
Han, Xintian; Goldstein, Mark; Ranganath, Rajesh

ID 41: Latent Temporal Flows for Multivariate Analysis of Wearables Data
Amiridi, Magda; Darnell, Gregory; Jewell, Sean

ID 43: An hybrid CNN-Transformer model based on multi-feature extraction and attention fusion mechanism for cerebral emboli classification
Vindas Yassine, Yamil E; Guépié, Blaise Kévin; Almar, Marilys; Roux, Emmanuel; Delachartre, Philippe

ID 49: EMIXER: End-to-end Multimodal X-ray Generation via Self-supervision
Biswal, Siddharth; Zhuang, Peiye; Pyrros, Ayis; Siddiqui, Nasir; Koyejo, Sanmi; Sun, Jimeng

ID 50: Diagnosing Epileptogenesis with Deep Anomaly Detection
Farahat, Amr; Lu, Diyuan; Bauer, Sebastian; Neubert, Valentin; Costard, Lara; Rosenow, Felix; Triesch, Jochen

ID 51: Disparate Censorship & Undertesting: A Source of Label Bias in Clinical Machine Learning
Chang, Trenton; Sjoding, Michael; Wiens, Jenna

ID 53: EHR Safari: Data is Contextual
Boag, Willie; Oladipo, Mercy; Szolovits, Peter

ID 57: A Multi Instance Learning Approach for Critical View of Safety Detection in Laparoscopic Cholecystectomy
Colbeci, Yariv; Zohar, Maya; Neimark, Daniel; Asselmann, Dotan; Bar, Omri

ID 59: Anomaly Detection in Echocardiograms with Dynamic Variational Trajectory Models
Ryser, Alain; Manduchi, Laura; Laumer, Fabian; Michel, Holger ; Wellmann, Sven; Vogt, Julia

ID 61: How fair is your graph? Exploring fairness concerns in neuroimaging studies
Ribeiro, Fernanda L; Shumovskaia, Valentina; Davies, Thomas O M; Ktena, Ira

ID 64: MedFuse: Multi-modal fusion with clinical time-series data and chest X-ray images
Hayat, Nasir; Geras, Krzysztof J; Shamout, Farah E

ID 65: Debiasing Deep Chest X-Ray Classifiers using Intra- and Post-processing Methods
Marcinkevičs, Ričards; Ozkan, Ece; Vogt, Julia

ID 80: ICE-NODE: Integration of Clinical Embeddings with Neural Ordinary Differential Equations
Alaa, Asem; Mayer, Erik; Barahona, Mauricio

ID 83: Weakly Supervised Deep Instance Nuclei Detection using Points Annotation in 3D Cardiovascular Immunofluorescent Images
Moradinasab, Nazanin; Sharma, Yash; Shankman, Laura; Owens, Gary; Brown, Donald

Posters B:

ID 84: auton-survival: an Open-Source Package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Event Data
Nagpal, Chirag; Potosnak, Willa; Dubrawski, Artur

ID 86: AudiFace: Multimodal Deep Learning for Depression Screening
Flores, Ricardo; Tlachac, ML; Toto, Ermal; Rundensteiner, Elke A

ID 93: Reinforcement Learning For Sepsis Treatment: A Continuous Action Space Solution
Huang, Yong; Cao, Rui; Rahmani, Amir

ID 104: Learning Optimal Summaries of Clinical Time-series with Concept Bottleneck Models
Wu, Carissa; Parbhoo, Sonali; Havasi, Marton; Doshi-Velez, Finale

ID 114: Classifying Unstructured Clinical Notes via Automatic Weak Supervision
Gao, Chufan; Goswami, Mononito; Chen, Jieshi; Dubrawski, Artur

ID 118: KCRL: A Prior Knowledge Based Causal Discovery Framework With Reinforcement Learning
Hasan, Uzma; Gani, Md Osman

ID 119: Error Amplification When Updating Deployed Machine Learning Models
Adam, George A; Chang, Chun-Hao; Haibe-Kains, Benjamin; Goldenberg, Anna

ID 121: Development and Validation of ML-DQA – a Machine Learning Data Quality Assurance Framework for Healthcare
Mark Sendak, Gaurav Sirdeshmukh, Timothy Ochoa, Hayley Premo, Linda Tang, Kira Niederhoffer, Sarah Reed, Kaivalya Deshpande, Emily Sterrett, Melissa Bauer, Laurie Snyder, Afreen Shariff, David Whellan, Jeffrey Riggio, David Gaieski, Kristin Corey, Megan Richards, Michael Gao, Marshall Nichols, Bradley Heintze, William Knechtle, William Ratliff, Suresh Balu

ID 126: Reducing Reliance on Spurious Features in Medical Image Classification with Spatial Specificity
Saab, Khaled K; Hooper, Sarah; Chen, Mayee; Zhang, Michael; Rubin, Daniel; Re, Christopher

ID 128: Searching for Fine-Grained Queries in Radiology Reports Using Similarity-Preserving Contrastive Embedding
Syeda-Mahmood, Tanveer; Shi, Luyao

ID 129: SurvLatent ODE : A Neural ODE based time-to-event model with competing risks for longitudinal data improves cancer-associated Venous Thromboembolism (VTE) prediction
Moon, Intae; Groha, Stefan; Gusev, Alexander

ID 130: Why predicting risk can’t identify ‘risk factors’: empirical assessment of model stability in machine learning across observational health databases
Markus, Aniek; Rijnbeek, Peter; Reps, Jenna M

ID 131: Few-Shot Learning with Semi-Supervised Transformers for Electronic Health Records
Poulain, Raphael; Gupta, Mehak; Beheshti, Rahmatollah

ID 135: Evaluating Uncertainty-Based Deep Learning Explanations for Prostate Lesion Detection
Trombley, Christopher M; Gulum, Mehmet A; Ozen, Merve; Aksamoglu, Melih; Esen, Enes; Kantardzic, Mehmed

ID 139: ALGES: Active Learning with Gradient Embeddings for Semantic Segmentation of Laparoscopic Surgical Images
Aklilu, Josiah; Yeung, Serena

Posters C (Clinical Abstracts):

ID 7: A machine learning approach to diagnose blood diseases
Luchinin, Alexander; Kolupaev, Oleg

ID 8: A logistic regression-based model to predict ICU mortality: problems and solutions
Luchinin, Alexander; Kolupaev, Oleg; Lyanguzov, Alexey

ID 16: Learning from failure: Explaining clinical ML model prediction errors
Li, Anthony; Huang, Zhilian; Oei, Chien Wei; Lian, Weixiang; Zhang, Xiaojin; Phua, Hwee Pin; Ng, Wei Xiang; Tay, Seow Yian

ID 17: Structured Understanding of Assessment and Plans in Clinical Documentation
Stupp, Doron; Barequet, Ronnie; Lee, I-Ching; Feder, Amir; Oren, Eyal; Benjamini, Ayelet; Hasidim, Avinatan; Matias, Yossi; Ofek, Eran; Rajkomar, Alvin

ID 18: PyMSM: Python package for Competing Risks and Multi-state models for Survival Data
Rossman, Hagai; Keshet, Ayya; Gorfine, Malka

ID 30: PyDTS: A Python Package for Discrete Time Survival Analysis with Competing Risks
Meir, Tomer; Gutman, Rom; Gorfine, Malka

ID 33: Temporal Patterns of Primary Care Utilization as Predictors for ICU Admission
Post, Benjamin JS; Brett, Stephen; Faisal, Aldo

ID 39: Utilizing a machine learning mortality model to increase serious illness conversations in hospitalized patients: A cluster randomized controlled trial
Ma, Jessica; Gao, Michael; Walter, Jonathan; Acker, Yvonne; Setji, Noppon; Olsen, Maren; Sendak, Mark; Balu, Suresh; Casarett, David

ID 40: Implementation of a machine learning algorithm to enhance primary care effectiveness and equity for peripheral arterial disease: a qualitative study
Wang, Sabrina; Hogg, Jeffry; Sangvai, Devdutta; Patel, Manesh; Kellogg, Kate; Balu, Suresh; Sendak, Mark

ID 42: Impact of AI dose suggestions on the prescriptions of ICU doctors
Nagendran, Myura; Gordon, Anthony; Faisal, Aldo

ID 48: CyclOps: A unified framework for data extraction and rigorous evaluation of ML models for clinical use-cases
Subasri, Vallijah; Krishnan, Amrit; Mckeen, Kaden; Dolatabadi, Elham

ID 63: Improving Equity and Value of Peripheral Artery Disease Care at a Population Level
Shen, Rebecca; Weissler, Elizabeth H; Ratliff, William; Hintze, Bradley; Nichols, Marshall; Gao, Michael; Cohen, Pam; Alvarado, Holly; Sendak, Mark; Balu, Suresh; Jones, Schuyler

ID 71: Development and validation of a convolutional neural network to identify regions of interest in lumpectomy margins using optical coherence tomography
Krishnamurthy, Savitri; Rempel, David; Berkeley, Andrew; Nagi, Chandandeep; Pekar, Vladimir; Burns, Margaret; Rabindran, Beryl; Nazarullah, Alia; Jatoi, Ismail; Hunt, Kelly; Thompson, Alastair

ID 73: Integration of a Post-operative Opioid Calculator into an Academic Gynecologic Surgery Practice
Zanolli, Nicole C; Knechtle, William; Sendak, Mark; Havrilesky, Laura; Davidson, Brittany

ID 78: Algorithm Development for Duke Emergency Pre-hospital Capacity Management
Shen, Rebecca; Ratliff, William; Knechtle, William; Joiner, Anjni; Godfrey, Andrew; Boyd, Joshua; Theiling, Jason; Kapadia, Neel; Sendak, Mark; Balu, Suresh; Burrows, Brian

ID 81: Development of a Machine Learning Model for Early Detection of Pediatric Sepsis
Tang, Linda Y; Ratliff, William; Sendak, Mark; Gao, Michael; Nichols, Marshall; Yashar, Faraz; Balu, Suresh; Subramanian, Neel; Uhl, Tammy; Denis, Liset; Sterrett, Emily

ID 82: A Geriatric-Specific Morbidity and Mortality Risk Stratification Tool
Premo, Hayley; Knechtle, William; Shi, Harvey; Sendak, Mark; Nichols, Marshall; Gao, Michael; Hintze, Bradley; Balu, Suresh; Rachakonda, Sai; McDonald, Shelley; Blitz, Jeanna; Lagoo-Deenadayalan, Sandhya; Kazaure, Hadiza

ID 85: Creating an evidence standards framework for artificial intelligence enabled digital health technologies
Macdonald, Trystan; Sounderajah, Viknesh; Unsworth, Harriet; Wolfram, Verena; Dillon, Bernice; Salmon, Mark; Liu, Xiao; Denniston, Alastair; Ashrafian, Hutan; Ashurst, Carolyn; Darzi, Ara; Holmes, Chris; Weller, Adrian

ID 90: STANDING Together: STANdards for Data Diversity, Inclusivity and Generalisability
Alderman, Joseph E; Palmer, Jo; Sebire, Neil; Ghassemi, Marzyeh; Calvert, Melanie; McCradden, Melissa; Kuku, Stephanie; Matin, Rubeta; Manohar, Sinduja; Espinosa, Cyrus; Gath, Jacqui; Denniston, Alastair; Liu, Xiaoxuan

ID 91: The Medical Algorithmic Audit: a protocol for safety monitoring of a skin cancer detection artificial intelligence health technology
Kale, Aditya U; Liu, Xiao; Denniston, Alastair

ID 92: Med-BERT v2: clinical foundation model on standardized secondary clinical data
Rasmy, Laila; Zhi, Degui

ID 94: A machine learning-based approach to classifying a provider’s description of chest pain
Donath, Elie; Cheney, Nicholas; Li, Yao

ID 100: Patient and Room Activity Video Summary (PRAVS) in the ICU: Rapidly Interpretable, ML-Generated Clinical Video Summaries of the Overnight Period
Parker, Samantha; Gilstrap, Daniel ; Bedoya, Armando; Lee, Patty; Gabriel, Paolo; Urbisci, Laura; Hu, Dewei; Troy, Tyler; Hata, Tom; Singh, Narinder; Choma, Michael

ID 101: Predicting Hospital Admissions and Emergency Department Visits in Patients Receiving Immune Checkpoint Inhibitors
Niederhoffer, Kira; Knechtle, William; Ratliff, William; Sendak, Mark; Gao, Michael; Nichols, Marshall; Hintze, Bradley; Revoir, Mike; Diamond, Carrie; Zafar, Yousuf; Clarke, Jeffrey; Uronis, Hope; Balu, Suresh; Shariff, Afreen

ID 105: EHR phenotyping by Natural Language Processing improves detection of patients at risk for preeclampsia
Wong, Melissa S; Wells, Matthew; Parrinella, Kristin; Gregory, Kimberly

ID 108: Phenotype Development and Validation for a Maternal Early Warning System
Richards, Megan E

ID 109: Single-Cell Phenotyping Using Optical Imaging and Artificial Intelligence
Bhattacharya, Abhishek; Hollon, Todd C; Alber, Daniel

ID 111: Development of a Machine Learning Model for Prediction of Mortality in Lung Transplant Patients
Ochoa, Timothy N; Knechtle, William; Sendak, Mark; Ratliff, William; Gao, Michael; Balu, Suresh; Deshpande, Kaivalya; Klapper, Jacob; Bottiger, Brandi; Snyder, Laurie; Hartwig, Matthew

ID 112: Transparent and Distributed AI Prediction Modeling for Predicting Severity of Pediatric Covid
Suarez Saiz, Fernando; Dey, Sanjoy; Chakraborty, Prithwish; Ghalwash, Mohamed; meyer, pablo

ID 116: Predictive models for clopidogrel outcome using prescription records and diagnosis codes
Lee, In Gu; Kim, Samuel; Ban, Mijeong; Kim, Min; Chiang, Jane

ID 132: Drug repurposing of metformin for Alzheimer’s disease: Causal inference in medical records and complementary systems pharmacology for biomarker identification
Albers, Mark; Charpignon, Marie-Laure; Vakulenko-Lagun, Bella; Zheng, Bang; Magdamo, Colin; Su, Bowen; Rodriguez, Steve; Sokolov, Artem; Boswell, Sarah; Sheu, Yi-Han; Somai, Melek; Betensky, Rebecca; Middleton, Lefkos; Hyman, Bradley; Finkelstein, Stan; Welsch, Roy; Tzoulaki, Ioanna; Blacker, Deborah; Das, Sudeshna

ID 134: Sources of bias in artificial intelligence that perpetuate healthcare disparities—A global review
Celi, Leo; Cellini, Jacqueline; Charpignon, Marie-Laure; Dee, Edward; Dernoncourt, Franck; Eber, Rene; Mitchell, William; Moukheiber, Lama; Schirmer, Julian; Situ, Julia; Paguio, Joseph; Park, Joel; Gichoya, Judy W; Yao, Seth

ID 138: Neurosurgical Ethomics: Using Machine Learning to Decode the Language of Neurosurgery
Nimer, Amr