Aplicaciones de la inteligencia artificial en el diagnóstico médico basado en datos

Abstract

Artificial intelligence (AI) has revolutionized medical diagnosis by improving accuracy and efficiency in disease identification, especially through the analysis of medical images and the use of deep learning models. This study aims to examine the main AI models applied in clinical diagnosis, their impact on diagnostic accuracy and the ethical challenges associated with their implementation. For this purpose, a systematic review of scientific articles indexed in Scopus between 2020 and 2025 was performed, using specific keywords related to artificial intelligence and data-driven medical diagnosis. The results showed that AI has reduced analysis times, optimized the early detection of pathologies and decreased the rate of diagnostic errors. However, challenges remain, such as the quality and representativeness of the data, the lack of explainability of some algorithms and the need for specialized training for healthcare professionals. In addition, regulation and standards for medical liability in the use of AI are still under development. In conclusion, AI has significant potential in medicine, but its adoption requires strategies to ensure its fairness, safety, and acceptance in the clinical setting.

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