ReviewMycoses2026
Infrared Spectroscopy as a Promising Tool for Diagnosing and Typing Human Pathogenic Fungi.
Review in Mycoses, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Rapid identification of feline sporotrichosis by ATR-FTIR spectroscopy coupled with machine learning.Analytical and bioanalytical chemistry · 2026Article
- Fourier transform infrared spectroscopy enables rapid strain typing inJournal of clinical microbiology · 2026Article
- UnmaskingPathogens (Basel, Switzerland) · 2026Article
- Differentiation ofFrontiers in microbiology · 2026Article
- Infrared Spectroscopy as a Promising Tool for Diagnosing and Typing Human Pathogenic Fungi.Mycoses · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Fungal infections are increasingly recognised as a global health challenge, responsible for millions of cases annually and substantial mortality, especially in immunocompromised individuals. Yet, the diagnosis of these infections remains notoriously difficult, often delayed by slow culture-based methods or hindered by the high cost and infrastructure demands of molecular diagnostics. In recent years, infrared (IR) spectroscopy has emerged as a promising alternative, offering rapid, cost-effective and reagent-free identification of human pathogenic fungi. This review provides an in-depth examination of how IR-based techniques, specifically, mid-infrared (MIR) and near-infrared (NIR) spectroscopy, are being applied in medical mycology. We explore the underlying chemical principles and highlight how recent advances in multivariate analysis and machine learning have enhanced their diagnostic accuracy. Studies have demonstrated the capacity of IR spectroscopy to accurately identify and type major fungal pathogens, while also providing insights into antifungal resistance profiles and outbreak tracking. While challenges remain, particularly regarding protocol standardisation and expansion of spectral databases, IR spectroscopy stands out as a valuable diagnostic strategy, especially in resource-limited settings. By reducing diagnostic time and cost, and expanding accessibility, IR-based methods have the potential to transform the clinical management of fungal infections, contributing to faster decision-making and improved patient outcomes.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.