ML4H Abstract Track 2020
Emily Alsentzer, Matthew B. A. McDermott, Fabian Falck, Suproteem K., Sarkar, Subhrajit Roy, Stephanie L. Hyland
TL;DR
This paper compiles abstracts from the ML4H workshop at NeurIPS 2020, showcasing diverse machine learning applications in health, though not all abstracts are included due to opt-outs.
Contribution
It provides a curated collection of recent research abstracts in machine learning for health from a major conference.
Findings
Diverse health-related ML applications presented
Highlights emerging trends in ML for health
Includes innovative methodologies and results
Abstract
A collection of the accepted abstracts for the Machine Learning for Health (ML4H) workshop at NeurIPS 2020. This index is not complete, as some accepted abstracts chose to opt-out of inclusion.
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Taxonomy
TopicsRadiomics and Machine Learning in Medical Imaging