Rapid fungal diagnostics utilizing genomic techniques and artificial intelligence

Abstract

Despite its high morbidity and mortality rates, invasive fungal infections are one of the most common infections in clinical care today, in part due to the lack of rapid and sensitive diagnostic techniques. Over the past few years, new genomic technologies such as next-generation sequencing, metagenomic sequencing, and CRISPR-based assays, paired with artificial intelligence (AI), have revolutionized fungal diagnostics by introducing culture-independent, rapid, and accurate pathogen detection. Automated data analysis, species identification, antifungal resistance prediction, and clinical decision support are additional strengths of AI in the field of diagnostics. This review highlights the latest developments in genomic and AI-driven fungal diagnostics, their clinical uses and the challenges that still lie ahead, as well as their future prospects for precision diagnostics and tailored treatment for individual patients.