Next-Generation Microbe Detection: The Role of Artificial Intelligence in the Diagnostic Modern Microbiology
Year: 2025
Type: article
Abstract: Artificial Intelligence (AI) is transforming clinical microbiology, especially microbe identification. With the advances in computational biology, machine learning (ML), and deep learning (DL), AI tools are emerging to speed up, improve the accuracy of, and make microbial diagnostics more efficient. These instruments process sophisticated biological information such as genomic sequences, microscopy images, spectrometry results, and patient metadata, thus allowing for accurate identification of pathogens. The numerous AI applications in the identification of microbes, such as genome-based prediction, automatic image analysis, mass spectrometry data analysis, and point-of-care diagnostic tools, are discussed in this review. The advantages, drawbacks, and future directions of AI in microbiology are also addressed. Key Words: Artificial Intelligence (AI), Clinical Microbiology, Machine Learning (ML), Deep Learning (DL), Computational Biology, Microbial Diagnostics, Pathogen Identification
DOI: 10.55041/ijsrem51354
Author: Sakib Alam Halder
Language: English
Subfield: Clinical Biochemistry
Domain: Life Sciences
Open Access status: bronze
OpenAlex ID: W4412364327