Applications of Artificial Intelligence in Clinical Practice and Healthcare (2010–2025): A Systematic Review

Abstract

Artificial intelligence (AI) is becoming increasingly important in modern healthcare due to its innovative approaches to diagnosis, therapy personalization, and patient care.  This systematic study, which draws on peer-reviewed literature from 2010 to 2025, looks at the current state of AI applications in clinical practice and healthcare.  14 of the 3,476 studies discovered using databases such as PubMed, The Lancet, and Scopus eventually met the inclusion criteria outlined in the PRISMA guidelines. According to the study, AI frequently outperforms traditional diagnostic methods in diseases such as breast cancer, melanoma, diabetic retinopathy, and pneumonia. Artificial intelligence helps clinicians make decisions by forecasting therapy responses based on genetic data and electronic health records. Tools like CURATE.AI and AI-powered warfarin dosing systems have potential for optimizing drug therapy and improving safety. Furthermore, virtual health technologies improve access and continuity of care, while artificial intelligence-powered predictive analytics identify high-risk patients for chronic diseases and hospital readmissions.   Despite its expanding importance, AI integration in healthcare confronts numerous hurdles, including data privacy concerns, ethical consequences, and the need for physician education.  The study emphasizes the need for artificial intelligence to enhance, rather than replace, healthcare staff, paving the way for more precise, rapid, and individualized treatment delivery.