Authors: Deepa Barethiya, Himani Shirpurkar, Drushti Dharmik
Abstract: Artificial Intelligence (AI) is increasingly integrated into clinical decision-making, particularly in disease-based treatment selection. AI systems promise efficiency, predictive accuracy, and personalized care by analyzing large datasets and recommending tailored therapies. However, these benefits are accompanied by ethical challenges that must be addressed before widespread adoption. Issues of transparency, bias, accountability, privacy, and patient autonomy are consistently reported in recent literature [1][5]. This paper synthesizes findings from 20 peer-reviewed studies published between 2023 and 2026, offering a systematic review of ethical concerns and governance strategies. By combining thematic analysis with case studies in oncology, cardiology, infectious disease, and neurology, we propose a framework for ethically responsible AI deployment in healthcare.
