Accepted Papers


Poster Session I:

  • Differentially Private Federated Learning for Medical Image Analysis [poster] [Zoom Link] - Mohammed Adnan (University of Guelph/Vector Institute)*; Jesse Cresswell (Layer 6 AI); Shivam Kalra (KIMIA Lab, University of Waterloo); Graham Taylor (University of Guelph); Hamid R Tizhoosh (University of Waterloo)
  • A Novel Interaction-based Methodology Towards Explainable AI with Better Understanding of Pneumonia Chest X-ray Images [poster] [Zoom Link] - Yiqiao Yin (Columbia University)
  • ADADL : Automatic Dementia Identification Model based on Activities of Daily Living using Smart Home Sensor data [poster] [Zoom Link] - Donghun Yang (Korea Institute of Science and Technology Information)*; Myunggwon Hwang (Korea Institute of Science and Technology Information)
  • Towards Trustworthy Cross-patient Model Development [poster] [Zoom Link] - Ali El-Merhi (Sahlgrenska Academy); Helena Odenstedt Herges (Sahlgrenska Academy); Linda Block (Sahlgrenska Academy); Mikael Elam (Sahlgrenska Academy); Jaquette Liljencrantz (Sahgrenska Academy); Miroslaw Staron (Chalmers | University of Gothenburg)*
  • Evaluating Policies for Sepsis Management: Decomposing Value Estimates Using Prototypes [poster] [Zoom Link] - Anton Matsson (Chalmers University of Technology)*; Fredrik Johansson (Chalmers University of Technology)
  • Deploying clinical machine learning? Consider the following... [poster] - Charles Lu (Massachusetts General Hospital / Harvard Medical School)*; Ken Chang (Massachusetts General Hospital); Praveer Singh (MGH / Harvard Medical School); Stuart Pomerantz (MGH-BWH CCDS); Sean Doyle (MGH-BWH CCDS); Sujay Kakarmath (Mass General Brigham); Christopher P Bridge (QTIM); Jayashree Kalpathy-Cramer (Massachusetts General Hospital)
  • Principled and Data Efficient Support Vector Machine Training Using the Minimum Description Length Principle, with Application in Breast Cancer Prediction - Harsh Singh (IIIT–Naya Raipur); Ognjen Arandjelovic (University of St Andrews)
  • A Whole-Slide is Greater Than the Sum of Its...Patches - Ria Chakrabarti (University of St Andrews); Ognjen Arandjelovic (University of St Andrews)*
  • Nuances of Interpreting X-ray Analysis by Deep Learning and Lessons for Reporting Experimental Findings - Steinar Valsson (University of St Andrews); Ognjen Arandjelovic (University of St Andrews)
  • Trusting Machine Learning Results from Medical Procedures in the Operating Room - Ali El-Merhi (Sahlgrenska University Hospital | University of Gothenburg)*; Miroslaw Staron (Chalmers | University of Gothenburg)
  • Predicting the impact of treatments over time with uncertainty aware neural differential equations - Edward De Brouwer (KU Leuven)*; Javier Gonzalez (Microsoft); Stephanie Hyland (Microsoft Research)
  • Poster Session II:

  • Semi-supervised Feature Selection for Efficient Detection of Systemic Deviations to Develop Trustworthy AI [poster] [Zoom Link] - Girmaw Abebe Tadesse (IBM Research)*; William Ogallo (IBM Research); Aisha Walcott-Bryant (IBM Research - Africa); Skyler D Speakman (IBM Research)
  • Eliminating race-related shortcuts in deep neural networks for chest X-ray analysis [poster] [Zoom Link] - Ryan Reui-En Wang (National Tsing Hua University); Li-Ching Chen (National Tsing Hua University); Pei-Chuan Lin (National Tsing Hua University); Judy Wawira (Emory Radiology); Leo Celi (MIT); Po-Chih Kuo (National Tsing Hua University)*
  • 3D-OOCS: Learning Prostate Segmentation with Inductive Bias [poster] [Zoom Link] - Shrajan Bhandary (TU Wien)*; Zahra Babaiee (TU Wien); Dejan Kostyszyn (Medical Center Albert-Ludwigs-University Freiburg im Breisgau); Tobias Fechter (Division of Medical Physics, Department of Radiation Oncology, University Mecical Centre Freiburg); Constantinos Zamboglou (Medical Center - University of Freiburg); Anca L Grosu (Department of Radiation Oncology, University Medical Center Freiburg); Radu Grosu (TU Wien)
  • Sparse Feature Interactions for Interpretable Healthcare Decision-Making [poster] [Zoom Link] - James Enouen (University of Southern California); Yan Liu (University of Southern California)
  • Interpret Your Care: Predicting the Evolution of Symptoms for Cancer Patients [poster] [Zoom Link] - Rupali Bhati (Universite Laval)*; Jennifer Jones (University of Toronto); Audrey Durand (Université Laval)
  • Explainable and Interpretable Diabetic Retinopathy Classification Based on Neural-Symbolic Learning [poster] [Zoom Link] - Se-In JANG (Massachusetts General Hospital and Harvard Medical School)*; Michaël J.A. Girard (Singapore Eye Research Institute); Alex Thiery (National University of Singapore)
  • Fairness in Kidney Exchange Programs: The Nash Social Welfare ProgramPerspective [poster] [Zoom Link] - William St-Arnaud (Université de Montréal)*; Margarida Carvalho (Université de Montréal); Golnoosh Farnadi (Mila, Université de Montréal)
  • A Pseudo Value Based Interpretable Neural Additive Model for Survival Analysis [poster] [Zoom Link] - Md Mahmudur Rahman (University of Maryland Baltimore County)*; Sanjay Purushotham (University of Maryland, Baltimore County)
  • Creating an Explainable Artificial Intelligence Framework to Increase Nurses’ Confidence in an Interhospital Transfer Scenario [poster] [Zoom Link] - Hyunggu Jung (University of Seoul)*; Hyungbok Lee (Seoul National University); Jinsun Jung (Seoul National University); Hyeoneui Kim (Seoul National University)
  • Two-step adversarial debiasing with partial learning - medical image case-studies [poster] [Zoom Link] - ramon correa ( Arizona State University )
  • CausalFedBlock : Decentralized causal federated learning with fair incentivization - Sreya Francis (MILA - Montreal Institute of Learning Algorithms)*
  • FedICE - Federated Invariant Cause Effect Estimation - Sreya Francis (MILA - Montreal Institute of Learning Algorithms)*