ARTIFICIAL INTELLIGENCE APPLICATIONS IN CLINICAL MICROBIOLOGY LABORATORY

Abstract

Artificial intelligence is becoming an increasingly important component of clinical microbiology informatics. Researchers, microbiologists, laboratorians, and diagnosticians are interested in AI-based testing because these applications have the potential to improve the turnaround time, quality, and cost of a test. Artificial intelligence which has gained importance in the laboratory, is used to support decision-making, identification and antimicrobial susceptibility testing with various technologies, image analyses, and MALDI-TOF-MS in medical microbiology and in infectious disease testing. Treatment of infections requires rapid and accurate identification and antimicrobial susceptibility testing. Modern artificial intelligence (AI) and machine-learning (ML) methods can now complete tasks with performance characteristic comparable to those of expert human operators. As a result, many healthcare fields combine these technologies, including in vitro diagnostics and, more broadly laboratory medicine, incorporate these technologies. These technologies are rapidly being developed and disclosed, but by comparison, their application so far has been limited. We need to further establish best practices and improve our information system and communications infrastructure to promote the implementation of reliable and advanced machine learning-based technologies. İnvolvement of the clinical microbiology laboratory community is essential to ensure that laboratory data is adequately accessible and thoughtfully incorporated into robust, safe and clinically effective ML-supported clinical diagnoses. This has been made possible by advances in modern computing and the widespread digitalization of health information. In this review, it is aimed to give information about to AI and its subfield of ML application areas in clinical microbiology laboratory.