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AI-Driven Risk Management & Optimization in Healthcare Supply Chain: A Machine Learning Approach

Year: 2025

Type: article

Abstract: The increasing complexity of healthcare supply chains (HSCs) has introduced significant risks, including cyber threats, disruptions, and inefficiencies. This paper explores the application of artificial intelligence (AI) and machine learning (ML) in risk management for healthcare supply chains. AI-driven models enhance predictive analytics, optimize inventory management, and mitigate disruptions by analyzing vast datasets in real time. This study reviews existing literature discusses AI-based risk assessment frameworks and presents a methodology for implementing machine learning techniques in HSC risk management. Future considerations highlight AI's role in enhancing security, resilience, and operational efficiency within healthcare logistics.

Source: Journal of Artificial Intelligence General science (JAIGS)

DOI: 10.60087/jaigs.v8i02.394

Authors: Md Imran Khan, Rasmila Lama, Kazi Saiful Islam, Md Rezaul Karim, Birbal Tamang

Institutions: Trine University, Lamar University

Language: English

Topic: Supply Chain Resilience and Risk Management

Subfield: Strategy and Management

Field: Business, Management and Accounting

Domain: Social Sciences

SDGs: Good health and well-being, Industry, innovation and infrastructure

Open Access status: hybrid

OpenAlex ID: W4413235440

FWCI: 1.832

Cites:

Cited by: 2

Related to: 10