Reinforcement learning for intelligent healthcare applications: A survey
Abstrak
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.
Topik & Kata Kunci
Penulis (4)
A. Coronato
Muddasar Naeem
G. Pietro
Giovanni Paragliola
Akses Cepat
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- 2020
- Bahasa
- en
- Total Sitasi
- 286×
- Sumber Database
- Semantic Scholar
- DOI
- 10.1016/J.ARTMED.2020.101964
- Akses
- Open Access ✓