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A Review on Application of Reinforcement Learning in Healthcare
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Author(s): Chitra A. Dhawale (P.R. Pote College of Engineering and Management, India)and Kritika Anil Dhawale (University of Technology Sydney, Australia)
Copyright: 2023
Pages: 15
Source title:
Cyber Trafficking, Threat Behavior, and Malicious Activity Monitoring for Healthcare Organizations
Source Author(s)/Editor(s): Dinesh C. Dobhal (Graphic Era University (Deemed), India), Sachin Sharma (Graphic Era University (Deemed), India), Kamlesh C. Purohit (Graphic Era University (Deemed), India), Lata Nautiyal (University of Bristol, UK)and Karan Singh (Jawaharlal Nehru University, India)
DOI: 10.4018/978-1-6684-6646-9.ch008
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Abstract
We are witnessing the era of data science where data is generating in an exponential manner. This big data is working as fuel to explore the business in every domain and healthcare is not the exception for this. Data analysis and data analytics in collaboration with machine learning techniques are playing an important role in every domain. Supervised and unsupervised approaches in machine learning depends on one shot, exhaustive, and reward output. Reinforcement learning (RL) handles these issues with sequential decision making problems, concurrent evaluation, and feedback methods. RL technique can be a suitable candidate for developing powerful solutions in a variety of healthcare domains. This chapter will focus on the broad applications of RL techniques in healthcare domains, which can be helpful to the researchers with systematic understanding of conceptual information, techniques, and an overview of RL applications in healthcare domains for various types of diseases right from chronic diseases and mental disorder.
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