Artificial Intelligence In Health Care: A Systematic Review Of Applications, Benefits, Challenges, And Ethical Implications

Abstract

ABSTRACT\r\nArtificial intelligence has become a rapidly expanding innovation in modern health care, influencing clinical practice, health-care administration, research, and public health systems. This systematic review, titled “Artificial Intelligence in Health Care: A Systematic Review of Applications, Benefits, Challenges, and Ethical Implications,” aimed to examine current evidence related to the use of AI in health care, with specific focus on its practical applications, benefits, implementation challenges, and ethical concerns. A structured literature search was conducted using Google Scholar, PubMed, ScienceDirect, SpringerLink, ResearchGate, and official health organization sources. Articles published mainly between 2020 and 2026 were reviewed, with selected foundational studies included where necessary. Relevant literature was selected based on its relation to AI in diagnosis, medical imaging, clinical decision support, electronic health records, patient monitoring, robotic surgery, drug discovery, telemedicine, health-care administration, patient safety, privacy, accountability, transparency, and ethical governance.\r\nThe review found that AI has significant potential to improve health-care delivery by supporting early diagnosis, enhancing diagnostic accuracy, assisting treatment planning, reducing clinical workload, improving resource utilization, and enabling personalized care. AI has shown particular usefulness in medical imaging, predictive analytics, electronic health record analysis, public health surveillance, and clinical decision support. However, the findings also revealed important challenges, including poor data quality, lack of explainability, algorithmic bias, privacy risks, cybersecurity threats, high implementation cost, limited staff training, and unclear legal accountability. Ethical concerns such as patient autonomy, informed consent, fairness, transparency, confidentiality, equity, and human oversight remain central issues in the safe use of AI.\r\nThe review concludes that AI should be used as a supportive tool rather than a replacement for health professionals. Safe and effective implementation requires clinical validation, ethical regulation, transparent algorithms, diverse data sets, professional training, patient involvement, and continuous monitoring. Future research should focus on real-world effectiveness, cost-effectiveness, bias reduction, patient outcomes, and responsible governance of AI in health care.\r\n