Summary
This narrative review examines recent developments in the diagnosis of invasive fungal infections, synthesising advances across molecular methods, serological techniques, biosensor technology, and artificial intelligence-based diagnostic models. The authors position these emerging tools as adjuncts to traditional diagnostic algorithms, addressing the clinical need for early and accurate diagnosis in immunocompromised patients. The review is notable for its comprehensive scope, integrating advances in biosensor technology and machine learning alongside molecular and serological methods in a single synthesis.
UK applicability
The diagnostic advances reviewed are applicable to UK clinical mycology laboratories and NHS infectious disease services, though the review does not address UK-specific epidemiology or healthcare system implementation. UK adoption of these technologies would depend on regulatory approval, cost-effectiveness evaluation, and integration into existing diagnostic pathways.
Key measures
Diagnostic methodologies and their technological advances; no quantitative clinical outcome measures reported in abstract
Outcomes reported
The review synthesises recent advances in fungal diagnostic methods, spanning molecular techniques (PCR assays, NGS), serology-based approaches, biosensor technology, and machine learning models. It documents the evolution from traditional microscopy and culture-based methods to contemporary non-culture-based diagnostic tools for invasive fungal infections.
Topic tags
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