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Cited by 327Artificial Intelligence in Healthcare and EducationReinforcement Learning in RoboticsMachine Learning in Healthcare

The DOI matches its Crossref record; 197 of the 204 references it cites were found in a registry or an index.

Reinforcement learning for intelligent healthcare applications: A survey

Coronato, Antonio, Naeem, Muddasar, De Pietro, Giuseppe, Paragliola, Giovanni·2020·Artificial Intelligence in Medicine
DOI 10.1016/j.artmed.2020.101964
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Abstract

Discovering new treatments and personalizing existing ones is one of the major goals of modern clinical research. In the last decade, Artificial Intelligence (AI) has enabled the realization of advanced intelligent systems able to learn about clinical treatments and discover new medical knowledge from the huge amount of data collected. Reinforcement Learning (RL), which is a branch of Machine Learning (ML), has received significant attention in the medical community since it has the potentiality to support the development of personalized treatments in accordance with the more general precision medicine vision. This report presents a review of the role of RL in healthcare by investigating past work, and highlighting any limitations and possible future contributions.

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Citations

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Show all 204 references

Research works printed but not linked: 29

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Metadata

Authors
Coronato, A., Naeem, M., De Pietro, G., & Paragliola, G.
Affiliations
  • National Research Council (IT)
  • Parthenope University of Naples (IT)
Corresponding author
Coronato, Antonio
ORCID
Venue
Artificial Intelligence in Medicine
Publisher
Elsevier BV
Published
2020-09
Volume
109
Pages
101964
ISSN
0933-3657 (ISSN-L)
DOI
10.1016/j.artmed.2020.101964
OpenAlex
W3090832565
Cited by
320
References
204
Citations by year
2026: 43 · 2025: 67 · 2024: 55 · 2023: 73 · 2022: 51 · 2021: 28 · 2020: 3
FWCI
11.57
Type
journal article
Language
en
Open access
closed
Licence
Locations
  • Artificial Intelligence in Medicine (publishedVersion)
  • PubMed (publishedVersion)
Funders
Ministero dell’Istruzione, dell’Università e della Ricerca
Topics
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Physical Sciences › Computer Science › Artificial Intelligence › Reinforcement Learning in Robotics
  • Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning in Healthcare
Keywords
reinforcement learning, medical applications, personalized treatment, precision medicine, clinical decision support, medical knowledge discovery
MeSH terms
Machine Learning, Artificial Intelligence, Delivery of Health Care, Reinforcement, Psychology, Precision Medicine

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