Highlights
- AI-based image recognition, particularly using ResNet-18, achieved over 99% accuracy in identifying key Aspergillus species from colony images.
- The approach offers a rapid, cost-effective, and expertise-light alternative to conventional identification methods.
- Diagnostic performance correlates with the distinctiveness of morphological features in fungal colonies.
- This technology holds promise for wider adoption in routine clinical mycology after further validation and database expansion.
Study Background and Disease Burden
