AI Revolutionizing Healthcare: Innovations, Challenges, and Ethical Considerations
Abstract
Artificial intelligence (AI) is increasingly transforming the healthcare landscape through innovative applications that leverage machine learning, deep learning and other data-driven techniques (Arefin, 2024). As complex datasets continue accumulating from diverse sources such as electronic health records, medical imaging, genomic sequencing and mobile health technologies, AI is well-positioned to derive insights and generate knowledge that can significantly benefit patients and clinicians. AI's capabilities in health analytics, clinical decision support, personalized treatment recommendations and automation of routine tasks hold much potential for advancing medicine and public health. By assisting in tasks such as medical image analysis, drug discovery, chronic disease management and population health surveillance, AI promises to make healthcare more predictive, pre-emptive, precise and participatory. However, developing and applying AI solutions in healthcare also presents important ethical challenges regarding data governance, algorithmic bias, clinical validity, explainability and its impacts on human jobs and skills. This paper aims to provide a comprehensive review of AI's applications and impacts across the healthcare sector, with a focus on core areas such as clinical medicine, biomedical research, health policy and workforce transformation. It will outline how various machine and deep learning techniques are enhancing specialties including radiology, pathology, genetics, as well as redefining roles like medical coding, administration and clinical workflows. The paper will also examine key considerations around privacy, security, bias and the human-AI collaboration model necessary to maximize AI's benefits in healthcare. An analysis of successful case studies and recommendations for policymakers will aim to guide more responsible development and adoption of AI for improved patient outcomes and health system performance.