Artificial Intelligence Applications in Decision Making for Disease Management 

preprint OA: closed CC-BY-4.0
📄 Open PDF View at publisher

Abstract

Background: Artificial intelligence (AI) has several potential applications in medicine, creating opportunities for reliable and evidence based decision making in disease management. Thus, the practical aspects of AI in decision-making should be identified. This study was conducted to identify AI applications in decision making for disease management. Method: This study was a systematic review using the PRISMA-ScR checklist. Data collection was carried out by searching the related keywords in WOS and Scopus in May 2023. Results: Regarding the AI applications in decision making for disease management, we found 80 sub-themes which were categorized into six themes, i.e. 1) Processing and managing data, 2) Characterization and analysis, 3) Prediction and risk stratification, 4) Screening, 5) Prognosis, and 6) Diagnosis. Conclusion: AI has considerable capability in disease treatment and would be an integral part of medicine in the future. This study clearly identified six main themes that addressed AI capability in decision making for disease management. The use of AI can help in making medical decisions with more trust and confidence and thus make medical interventions more accurate and effective.

My notes (saved in your browser only)

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. The paper's references may be in our DB but unresolved to ``paper_id`` (resolution happens at ingest when the cited DOI matches a row we already have). Run the cross-source citation reconcile pass to retry.

Source provenance

europepmc
last seen: 2026-05-19T01:45:01.086888+00:00
unpaywall
last seen: 2026-05-20T11:00:21.680559+00:00
License: CC-BY-4.0