Risks and limitations of using artificial intelligence in medicine

Le résumé fourni par la source

The scientific, technical, ethical, and legal aspects of applying artificial intelligence (AI) in modern medicine, as well as its impact on medical professionals and patients, are examined. The research methodology is based on the analysis of scientific publications dedicated to the use of AI in medicine. Systematization of the available data allows identifying key limitations faced by developers of medical AI systems and their users. These issues are related to the quality and completeness of the data on which machine learning models are built, the limited clinical context, challenges in knowledge generalization, and system interoperability. Ethical challenges include concerns about privacy, algorithmic bias, and the distribution of responsibility. Additionally, there are issues regarding the regulatory framework for AI in healthcare and the training of medical professionals in computer technologies. Overcoming these limitations requires improving data quality, developing multimodal systems, increasing algorithm transparency, and refining the regulatory framework.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.