The role of artificial intelligence and big data in health sciences research: Review of advances and educational perspectives

Abstract

Introduction: Artificial intelligence (AI) and big data have revolutionized research and education in Health Sciences between 2018 and 2022. They offer innovative tools for data analysis, medical diagnosis and treatment personalization. This article reviews the most significant advances in this field. Applications such as predictive medicine, the use of big data in public health and the integration of technologies in the training of health professionals are highlighted. Methodology: It was carried out using a documentary review approach. To do so, several scientific texts were consulted, with a predominance of original or review articles, published between 2018 and 2022. The sources came mainly from databases such as Scopus, Web of Science and Google Scholar and were processed through the bibliographic manager Zotero. Results: The COVID-19 pandemic accelerated the adoption of these tools, highlighting their potential and persistent challenges. The quality of data, teacher training and gaps in access to technological resources are highlighted; in the educational field, adaptive learning platforms and simulations based on real data have transformed teaching methods, although their implementation requires significant investments. In addition, the ethical and regulatory aspects associated with the use of AI and big data are discussed, and the need for global standards that protect privacy and avoid bias in algorithms is underlined. Conclusion: This integrative analysis provides a critical overview of how these technologies shape the present and future of health, identifying challenges and opportunities for their equitable and sustainable adoption.

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