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Invited Paper Session

Optimizing AI/ML for Medical Device and Clinical Trial: Bias Detection, Elimination, and Evaluation

Tue, Aug 5, 2:00 PM - 3:50 PM Room CC-209B Music City Center

GraceHyun KimOrganizerMartin WellsChair

Section on Medical Devices and Diagnostics co: Biometrics Section Applied

4 Presentations

Causal Clustering for Treatment-Heterogeneity-Driven Disease Subtyping: with an Application to a Cardiac Magnetic Resonance Imaging Study

2:05 PM - 2:30 PM

Xiaofeng Wang (The Cleveland Clinic Foundation)

Co-authors: Rui Ren (Department of Biostatistics, Yale University), Deborah Kwon (Cleveland Clinic)

Causal Machine Learning Clustering Medical Imaging Radiomics Treatment Optimization

Enhancing Fairness in Medical Diagnosis based on Deep Learning and Influence Score

2:30 PM - 2:55 PM

Henry Horng-Shing Lu (Kaohsiung Medical University and National Yang Ming Chiao Tung University)

Artificial Intelligence (AI)Deep Learning Fairness Medical Diagnosis Influence Score (I-score)Backward Dropping Algorithm

Misinterpretation of AI, Application of Domain Knowledge, and Attention in Selecting a Targeted Population for AI Training and Evaluation in Medical Imaging

2:55 PM - 3:20 PM

GraceHyun Kim (University of California-Los Angeles)

Artificial intelligence (AI)trustworthy AI (TAI)eXplainable AI (XAI)quantitative lung fibrosis information-driven quality control parameters

Optimizing Clinical Trial Design: The Role of AI in Boosting Inclusivity and Efficiency

3:20 PM - 3:45 PM

Ruishan Liu (University of Southern California)

Clinical Trials Artificial Intelligence (AI) Trial Enrollment Inclusivity

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