MLHC 2022

38 papers

ALGES: Active Learning with Gradient Embeddings for Semantic Segmentation of Laparoscopic Surgical Images

Josiah Aklilu, Serena Yeung

Evaluating Uncertainty-Based Deep Learning Explanations for Prostate Lesion Detection

Christopher M Trombley, Mehmet Akif Gulum, Merve Ozen, Enes Esen, Melih Aksamoglu

Few-Shot Learning with Semi-Supervised Transformers for Electronic Health Records

Raphael Poulain, Mehak Gupta, Rahmatollah Beheshti

Why predicting risk can’t identify ‘risk factors’: empirical assessment of model stability in machine learning across observational health databases

Aniek F. Markus, Peter R. Rijnbeek, Jenna M. Reps

SurvLatent ODE : A Neural ODE based time-to-event model with competing risks for longitudinal data improves cancer-associated Venous Thromboembolism (VTE) prediction

Intae Moon, Stefan Groha, Alexander Gusev

Searching for Fine-Grained Queries in Radiology Reports Using Similarity-Preserving Contrastive Embedding

Tanveer Syeda-Mahmood, Luyao Shi

Reducing Reliance on Spurious Features in Medical Image Classification with Spatial Specificity

Khaled Saab, Sarah Hooper, Mayee Chen, Michael Zhang, Daniel Rubin

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

Error Amplification When Updating Deployed Machine Learning Models

George Alexandru Adam, Chun-Hao Kingsley Chang, Benjamin Haibe-Kains, Anna Goldenberg

KCRL: A Prior Knowledge Based Causal Discovery Framework with Reinforcement Learning

Uzma Hasan, Md Osman Gani

Classifying Unstructured Clinical Notes via Automatic Weak Supervision

Chufan Gao, Mononito Goswami, Jieshi Chen, Artur Dubrawski

Learning Optimal Summaries of Clinical Time-series with Concept Bottleneck Models

Carissa Wu, Sonali Parbhoo, Marton Havasi, Finale Doshi-velez

Reinforcement Learning For Sepsis Treatment: A Continuous Action Space Solution

Yong Huang, Rui Cao, Amir Rahmani

AudiFace: Multimodal Deep Learning for Depression Screening

Ricardo Flores, ML Tlachac, Ermal Toto, Elke Rundensteiner

auton-survival: an Open-Source Package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Event Data

Chirag Nagpal, Willa Potosnak, Artur Dubrawski

Weakly Supervised Deep Instance Nuclei Detection using Points Annotation in 3D Cardiovascular Immunofluorescent Images

Nazanin Moradinasab, Yash Sharma, Laura S. Shankman, Gary K. Owens, Donald E. Brown

ICE-NODE: Integration of Clinical Embeddings with Neural Ordinary Differential Equations

Asem Alaa, Erik Mayer, Mauricio Barahona

Debiasing Deep Chest X-Ray Classifiers using Intra- and Post-processing Methods

Ričards Marcinkevičs, Ece Ozkan, Julia E. Vogt

MedFuse: Multi-modal fusion with clinical time-series data and chest X-ray images

Nasir Hayat, Krzysztof J. Geras, Farah E. Shamout

How fair is your graph? Exploring fairness concerns in neuroimaging studies

Fernanda Ribeiro, Valentina Shumovskaia, Thomas Davies, Ira Ktena

Anomaly Detection in Echocardiograms with Dynamic Variational Trajectory Models

Alain Ryser, Laura Manduchi, Fabian Laumer, Holger Michel, Sven Wellmann

A Multi Instance Learning Approach for Critical View of Safety Detection in Laparoscopic Cholecystectomy

Yariv Colbeci, Maya Zohar, Daniel Neimark, Dotan Asselmann, Omri Bar

EHR Safari: Data is Contextual

William Boag, Mercy Oladipo, Peter Szolovits

Disparate Censorship & Undertesting: A Source of Label Bias in Clinical Machine Learning

Trenton Chang, Michael W. Sjoding, Jenna Wiens

Diagnosing Epileptogenesis with Deep Anomaly Detection

Amr Farahat, Diyuan Lu, Sebastian Bauer, Valentin Neubert, Lara Sophie Costard

EMIXER: End-to-end Multimodal X-ray Generation via Self-supervision

Siddharth Biswal, Peiye Zhuang, Ayis Pyrros, Nasir Siddiqui, Sanmi Koyejo

An hybrid CNN-Transformer model based on multi-feature extraction and attention fusion mechanism for cerebral emboli classification

Yamil Vindas, Blaise Kevin Guepie, Marilys Almar, Emmanuel Roux, Philippe Delachartre

Latent Temporal Flows for Multivariate Analysis of Wearables Data

Magda Amiridi, Gregory Darnell, Sean Jewell

Survival Mixture Density Networks

Xintian Han, Mark Goldstein, Rajesh Ranganath

HiCu: Leveraging Hierarchy for Curriculum Learning in Automated ICD Coding

Weiming Ren, Ruijing Zeng, Tongzi Wu, Tianshu Zhu, Rahul G. Krishnan

GeoECG: Data Augmentation via Wasserstein Geodesic Perturbation for Robust Electrocardiogram Prediction

Jiacheng Zhu, Jielin Qiu, Zhuolin Yang, Douglas Weber, Michael A. Rosenberg

Learning Optimal Dynamic Treatment Regimes Using Causal Tree Methods in Medicine

Theresa Blumlein, Joel Persson, Stefan Feuerriegel

Ensembling Neural Networks for Improved Prediction and Privacy in Early Diagnosis of Sepsis

Shigehiko Schamoni, Michael Hagmann, Stefan Riezler

Density-Aware Personalized Training for Risk Prediction in Imbalanced Medical Data

Zepeng Huo, Xiaoning Qian, Shuai Huang, Zhangyang Wang, Bobak J. Mortazavi

Survival Seq2Seq: A Survival Model based on Sequence to Sequence Architecture

Ebrahim Pourjafari, Navid Ziaei, Mohammad R. Rezaei, Amir Sameizadeh, Mohammad Shafiee

Deep Cascade Learning for Optimal Medical Image Feature Representation

Junwen Wang, Xin Du, Katayoun Farrahi, Mahesan Niranjan

Unified Auto Clinical Scoring (Uni-ACS) with Interpretable ML models

Anthony Li, Ming Lun Ong, Chien Wei Oei, Weixiang Lian, Hwee Pin Phua

Contrastive Learning of Medical Visual Representations from Paired Images and Text

Yuhao Zhang, Hang Jiang, Yasuhide Miura, Christopher D. Manning, Curtis P. Langlotz