Sarcouncil Journal of Engineering and Computer Sciences

Abstract: Artificial intelligence (AI) has emerged in the contemporary healthcare sector for advanced diagnostic, prognostic, and treatment plan. But the emergence of the AI systems creates the new issue of dehumanisation of data-driven medicine. The reviewed paper addresses the concept of humanizing AI in healthcare analytics - a paradigm, which views interpretability, ethics, and contextual understanding as constituents of AI design and implementation. It covers the change in the reasoning of black-box models towards explainable AI (XAI) and, more generally, towards human-centered AI (HCAI), where empathy, inclusivity and ethical reasoning are becoming more and more a part of the computational systems. In the article, the author examines the significant progresses in radiology, cardiology, and electronic health record (EHR) analytics specifically in terms of the integration of multimodal data, interaction between humans and AI, as well as equitability. It also addresses some of the major issues, including algorithmic bias, accountability, privacy and sustainability, and alludes to governance efforts, including the WHO AI Ethics Framework and the EU AI Act. Finally, this review argues that the future practice of healthcare AI should not imitate human intelligence but rather enhance it by building systems that are technically powerful yet ethically oriented, situationally aware, and aligned with the fundamentals of patient-centered care.