Machine-Learning-Powered Information Systems: A Systematic Literature Review for Developing Multi-Objective Healthcare Management
Source abstract
Abstract
The incorporation of machine learning (ML) into healthcare information systems (IS) has transformed multi-objective healthcare management by improving patient monitoring, diagnostic accuracy, and treatment optimization. Notwithstanding its revolutionizing capacity, the area lacks a systematic understanding of how these models are divided and analyzed, leaving gaps in normalization and benchmarking. The present research usually overlooks holistic models for comparing ML-enabled ISs, significantly considering pivotal function criteria like accuracy, precision, sensitivity, and specificity. To address these gaps, we conducted a broad exploration of 306 state-of-the-art papers to present a novel taxonomy of ML-enabled IS for multi-objective healthcare management. We categorized these studies into six key areas, namely diagnostic systems, treatment-planning systems, patient monitoring systems, resource allocation systems, preventive healthcare systems, and hybrid systems. Each category was analyzed depending on significant variables, uncovering that adaptability is the most effective parameter throughout all models. In addition, the majority of papers were published in 2022 and 2023, with MDPI as the leading publisher and Python as the most prevalent programming language. This extensive synthesis not only bridges the present gaps but also proposes actionable insights for improving ML-powered IS in healthcare management.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Artificial Intelligence in Healthcare and Education · Machine Learning in Healthcare · Digital Mental Health Interventions
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Mechanical Engineering, University of Houston, Houston, TX 77004, USA
Department of Electrical Engineering, University of Cincinnati, Cincinnati, OH 45221, USA
Department of Computer Engineering and Information Technology, Sadjad Institute of Higher Education, Mashhad 9188148848, Iran
Department of Biomedical Engineering, University of Houston, Houston, TX 77004, USA
Independent Researcher, Tehran 1417614411, Iran
Department of Physics, City University of Hong Kong, Kowloon, Hong Kong SAR 999077, China
China Huadian Corporation Ltd. (CHD), Hong Kong SAR 999077, China
References (100+)
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