Artificial intelligence (AI) and medical microbiology: A narrative review

Abstract

Artificial Intelligence (AI) has transformed numerous domains, including the discipline of medical microbiology. Artificial intelligence is currently being used to assist in clinical decision-making and the monitoring of diseases, with the possibility of being used for genomic information and extensive digital datasets. Through the utilization of advanced algorithms, machine learning (ML), and deep learning (DL) methods, artificial intelligence (AI) can improve disease diagnoses, forecast outbreaks, and customize medical treatments. Moreover, AI is revolutionizing the field of medical and pharmaceutical microbiology, specifically in the areas of pathogen identification, development of point-of-care diagnostics, and drug discovery. Machine learning (ML) is of great use for image analysis since it improves the effectiveness and accuracy of clinical microbiology practice. Despite these developments, it is imperative to tackle issues related to the accuracy of data and limitations of algorithms. Additionally, it is crucial to focus on creating AI models that can be easily understood and interpreted. This review examines the present uses, advantages, and obstacles of AI in medical microbiology, emphasizing its revolutionary impact on enhancing healthcare results.