Machine Learning for Health (ML4H) Workshop at NeurIPS 2018
Natalia Antropova, Andrew L. Beam, Brett K. Beaulieu-Jones, Irene, Chen, Corey Chivers, Adrian Dalca, Sam Finlayson, Madalina Fiterau, Jason, Alan Fries, Marzyeh Ghassemi, Mike Hughes, Bruno Jedynak, Jasvinder S., Kandola, Matthew McDermott, Tristan Naumann, Peter Schulam
TL;DR
This collection of papers from the ML4H workshop at NeurIPS 2018 showcases recent advances in applying machine learning techniques to healthcare challenges, emphasizing new methods, applications, and insights in medical data analysis.
Contribution
The workshop presents novel machine learning approaches tailored for healthcare, highlighting interdisciplinary collaborations and innovative applications in medical research.
Findings
Improved predictive models for medical diagnosis
New algorithms for analyzing healthcare data
Enhanced understanding of ML applications in medicine
Abstract
This volume represents the accepted submissions from the Machine Learning for Health (ML4H) workshop at the conference on Neural Information Processing Systems (NeurIPS) 2018, held on December 8, 2018 in Montreal, Canada.
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Taxonomy
TopicsArtificial Intelligence in Healthcare