Applications of artificial intelligence in contemporary medical diagnosis
Keywords:
Artificial intelligence, medical diagnosis, machine learning, healthcare innovation, predictive medicine, digital health technologiesAbstract
Artificial intelligence has become one of the most significant technological transformations in contemporary healthcare, particularly in the field of medical diagnosis. The integration of intelligent systems into clinical environments has improved diagnostic accuracy, accelerated medical decision-making, optimized patient monitoring, and contributed to the modernization of healthcare systems worldwide. The objective of this study was to analyze the principal applications of artificial intelligence in contemporary medical diagnosis and evaluate its impact on healthcare delivery, clinical practice, and patient care. The study was developed using a qualitative analytical methodology supported by a comprehensive narrative review of scientific literature. Scientific publications, clinical investigations, and technological studies published between 2017 and 2026 were analyzed through recognized academic databases, including PubMed, Scopus, ScienceDirect, and Google Scholar. The results demonstrated that artificial intelligence significantly improves diagnostic precision, healthcare efficiency, disease prediction, and personalized medicine strategies. However, important challenges related to patient privacy, cybersecurity, algorithmic bias, and professional accountability were also identified. Furthermore, the study highlighted the importance of promoting an ethical, transparent, and responsible use of artificial intelligence, ensuring that these technologies function as clinical support tools rather than substitutes for physicians. Despite their advanced analytical capabilities, medical decision-making continues to depend on human judgment, empathy, and the physician-patient relationship.
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