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Efficient resource allocation in healthcare systems through deep learning and optimization science

Year: 2025

Type: article

Abstract: Efficient resource allotment in healthcare frameworks could be a basic challenge, particularly given the expanding request for quality care and constrained assets. This term paper investigates the integration of Deep learning and optimization science as a vigorous approach to address this challenge. Deep learning methods give precise expectations of healthcare requests, whereas optimization models help allocate resources powerfully and effectively. This cooperative energy empowers healthcare frameworks to play down costs, move forward understanding results, and improve generally framework proficiency. The paper talks about key strategies, case thinks about, and future inquire about bearings in applying Deep learning and optimization science to healthcare asset allotment.

Source: Journal of Information and Optimization Sciences

DOI: 10.47974/jios-1989

Authors: Vaishali V. Raje, Sukhvinder Singh Dari, Shrikrishna N. Bamne, Prasad B. Chaudhari, Trupti S. Bhosale, Girraj khandelwal, Vinit Khetani

Institutions: Krishna Institute of Medical Sciences, Krishna Institute of Medical Sciences Deemed University, Symbiosis International University, JECRC University

Language: English

Topic: Healthcare Operations and Scheduling Optimization

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: bronze

OpenAlex ID: W4411068445

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