reviewNature Biomedical EngineeringJul 4, 2022HYBRID OA

Shifting machine learning for healthcare from development to deployment and from models to data

AZAngela ZhangLXLei XingJZJames ZouJCJoseph C. Wu

Cardiovascular Institute of the South · Green University of Bangladesh · +3 more institutions

PubMed
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Abstract

In the past decade, the application of machine learning (ML) to healthcare has helped drive the automation of physician tasks as well as enhancements in clinical capabilities and access to care. This progress has emphasized that, from model development to model deployment, data play central roles. In this Review, we provide a data-centric view of the innovations and challenges that are defining ML for healthcare. We discuss deep generative models and federated learning as strategies to augment datasets for improved model performance, as well as the use of the more recent transformer models for handling larger datasets and enhancing the modelling of clinical text. We also discuss data-focused problems in the…

Citation impact

389
total citations
FWCI
49.11
Percentile
100%
References
146
Citations per year

Authors

4

Topics & keywords

Topics
Keywords
  • Software deployment
  • Computer science
  • Artificial intelligence
  • Health care
  • Machine learning
  • Generative grammar
  • Deep learning
  • Automation
UN Sustainable Development Goals
  • Industry, innovation and infrastructure
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