THE ETHICS OF AI IN HEALTHCARE: DIAGNOSES AND DECISION-MAKING
Keywords:
Artificial Intelligence, Healthcare Ethics, Diagnostics, Clinical, Decision-Making, Accountability, Algorithmic Bias, Transparency, Patient Autonomy, Data Privacy, Explainable AI, Human-in-the-Loop, EquityAbstract
This article provides an in-depth analysis of the ethical considerations surrounding the use of artificial intelligence (AI) in healthcare, with a focus on diagnostics and clinical decision-making. It examines challenges related to accountability, algorithmic bias, transparency, patient autonomy, and data privacy. Case studies, including AI applications in oncology, radiology, and hospital predictive analytics, illustrate both the potential benefits and the risks associated with AI integration. The article argues that while AI can improve diagnostic accuracy, efficiency, and patient outcomes, ethical oversight, human involvement, and regulatory frameworks are essential to ensure responsible and equitable implementation in healthcare.
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