Abstract: Objective To explore the pathogen distribution in patients with fungal infections, identify factors affecting the accuracy of fungal detection, and develop targeted control strategies.Methods A total of 700 fungal specimens were collected from Department of Laboratory Medicine, the First Affiliated Hospital of PLA Air Force Medical University, from August 2023 to August 2024. The distribution of fungal strains was analyzed. Logistic regression was used to identify factors influencing the accuracy of fungal detection, and a decision tree model was constructed based on risk factors to propose measures for improving detection accuracy.Results A total of 837 fungal strains were obtained from 700 specimens, with the major strains being Candida albicans (224 strains, 26.76%), Aspergillus fumigatus (147 strains, 17.56%), and Candida parapsilosis (131 strains, 15.65%). The detection results showed 789 correctly identified strains (94.27%) and 48 misidentified strains (5.73%). Multivariate logistic regression analysis indicated that the following are independent risk factors affecting the detection accuracy of fungal specimens: strain type (filamentous fungi), delayed specimen submission, inappropriate sampling site, insufficient specimen volume, non-compliant testing procedures, non-sterile environment, inadequate storage conditions, and improper use of equipment (P<0.05). The decision tree model selected the following six risk factors as model nodes: strain type, testing procedure, equipment usage, sterile environment, sampling site, and specimen volume, with strain type being the most important predictive factor. The model's classification accuracy reached 94.4%.Conclusions The detection accuracy varies among different fungal strains. Filamentous fungi, along with factors such as specimen submission, sampling, specimen volume, testing procedures, environment, storage, and equipment usage, are independent risk factors affecting detection accuracy. The laboratory department should develop precise control strategies for these risk factors, strengthen quality supervision of laboratory staff, specimen collection, and testing procedures to ensure accurate clinical test results and provide reliable evidence for the diagnosis and treatment of fungal infections.