Fungal infections pose a major global health concern, particularly among individuals with weakened immune system, due to their significant morbidity and mortality rates, as well as the escalating issue of antifungal resistance (AFR). These challenges highlight the pressing need for innovative solutions in diagnostics, resistance surveillance, and therapeutic interventions. Artificial intelligence (AI) presents a groundbreaking opportunity to tackle these issues by utilizing machine learning (ML) and deep learning (DL) to process complex datasets, identify hidden correlations, and optimize decision-making. This paper examines the application of AI in mycology, emphasizing its role in enhancing diagnostic precision, forecasting antifungal resistance, and accelerating drug discovery to improve patient care.

Title

2025 International Conference on Machine Intelligence and Smart Innovation (ICMISI)

Publisher

IEEE

Publisher Country

Egypt

Publication Type

Online only

Volume

--

Year

2025

Pages

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