Technology Platforms and Approaches for Building and Evaluating Machine Learning Methods in Healthcare.

Journal: The journal of applied laboratory medicine
Published Date:

Abstract

BACKGROUND: Artificial intelligence (AI) methods are becoming increasingly commonly implemented in healthcare as decision support, business intelligence tools, or, in some cases, Food and Drug Administration-approved clinical decision-makers. Advanced lab-based diagnostic tools are increasingly becoming AI driven. The path from data to machine learning methods is an active area for research and quality improvement, and there are few established best practices. With data being generated at an unprecedented rate, there is a need for processes that enable data science investigation that protect patient privacy and minimize other business risks. New approaches for data sharing are being utilized that lower these risks.

Authors

  • Sean D Mooney
    Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA.