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Automatic Identification of Clinically Important Aspergillus Species by Artificial Intelligence-Based Image Recognition Proof-Of-Concept Study by Nguyễn Hoàng Long is a document available to read on EtoBox.
This proof-of-concept study explores the use of artificial intelligence (AI) for the automatic identification of clinically important Aspergillus species through image recognition. Utilizing a dataset of images from four Aspergillus species, the study found that the ResNet-18 algorithm outperformed others with a testing accuracy of 99.35%. The findings suggest that AI-based image recognition could serve as a routine diagnostic tool in clinical laboratories due to its efficiency and low resource requirements
- Author
- Nguyễn Hoàng Long
- Language
- EN