PERSPECTIVAS FUTURAS DE LA INFECTOLOGÍA CLÍNICA IMPULSADA POR IA Y LA METAGENÓMICA.

Authors

Eduardo Andrés Rojas Portéz
Marcos Andrés Calva Torres
Catalina María Hurtado

Synopsis

Contemporary infectious disease medicine faces growing challenges due to the emergence of zoonotic pathogens and antimicrobial resistance. The integration of next-generation metagenomic sequencing (mNGS) and artificial intelligence (AI) is transforming infectious disease diagnosis and surveillance, shifting from a reactive to a predictive and preventive model. mNGS enables simultaneous identification of multiple microorganisms without prior hypotheses, while AI analyzes vast genomic datasets, predicts antimicrobial resistance, and anticipates epidemic outbreaks. This technological convergence enhances diagnostic sensitivity, supports digital surveillance, and accelerates the discovery of new drugs, such as Halicin, identified through deep neural networks. However, ethical and methodological challenges persist, including the need for explainable AI (XAI), regulatory validation, and data equity. Together, AI and mNGS are redefining infectious disease medicine toward a precision-based, personalized, and data-driven approach that strengthens clinical decision-making and public health responses in the 21st century.

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Pages

165-176

Published

April 21, 2026

How to Cite

PERSPECTIVAS FUTURAS DE LA INFECTOLOGÍA CLÍNICA IMPULSADA POR IA Y LA METAGENÓMICA. (2026). In INFECTOLOGÍA CLÍNICA TOMO 3 (pp. 165-176). Puerto Madero Editorial Académica. https://doi.org/10.55204/pmea.128.c200