Application of Artificial Intelligence in Clinical Microbiology: Current Status and Future Perspectives
Aplicación de la Inteligencia Artificial en Microbiología Clínica
DOI:
https://doi.org/10.15665/3xkv8c98Keywords:
Artificial Intelligence, Machine Learning, Convolutional Neural Network, SenSensitivity and MicrobiologyAbstract
Artificial intelligence (AI) mimics human capabilities such as reasoning and learning to analyze complex data. In clinical microbiology, traditional methods for identifying various microorganisms (parasites, bacteria, viruses, and fungi) have limitations such as low accuracy and delayed diagnosis. The objective of this study is to analyze the scientific evidence on the application of AI as a diagnostic tool in the identification of microorganisms. Through a narrative review of PubMed, Scopus, Elsevier, Scielo, and Google Scholar databases, 50 articles published between 2020 and 2025 in English and Spanish were selected. These articles focused on practical applications of AI in microbiology and were not merely theoretical. The results demonstrated that AI achieves diagnostic sensitivities of 95–100%, surpassing conventional human accuracy using advanced technological tools. In conclusion, the evidence supports the progressive incorporation of AI in clinical microbiology laboratories as a key strategy to improve the quality of care and optimize healthcare resources.
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