Artificial Intelligence (AI) is an emerging, transforming and revolutionary technology that has captured attention worldwide. It is translating research into precision oncology treatments. AI can analyse large or big data sets requiring high-speed specialized computing solutions. The data are big in terms of volume and multimodal with the amalgamation of images, text and structure. Machine learning has identified antifungal drug targets, and taxonomic and phylogenetic classification of fungi based on sequence analysis is now available. Real-time identification tools and user-friendly mobile applications for identifying fungi have been discovered. Akin to histopathology, AI can be applied to fungal cytology. AI has been fruitful in cytopathology of the thyroid gland, breast, urine and uterine cervical lesions. AI has a huge scope in fungal cytology and would certainly bear fruit with its accuracy, reproducibility and capacity for handling big data. The purpose of this systematic review was to highlight the AI's utility in detecting fungus and its typing with a special focus on future application in fungal cytology. We also touch upon the basics of AI in brief.

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人工智能：探索真菌检测和分型的实用性以及真菌细胞学的未来应用

人工智能（AI）是一项新兴的、变革性的、革命性的技术，引起了全世界的关注。它将研究转化为精准的肿瘤治疗。人工智能可以分析需要高速专业计算解决方案的大型数据集。数据量大、多模态、图像、文本和结构融合。机器学习已经确定了抗真菌药物靶点，并且现在可以基于序列分析对真菌进行分类学和系统发育分类。用于识别真菌的实时识别工具和用户友好的移动应用程序已经被发现。与组织病理学类似，人工智能可以应用于真菌细胞学。AI 在甲状腺、乳腺、尿液和宫颈病变的细胞病理学方面取得了丰硕的成果。人工智能在真菌细胞学领域有着广阔的应用前景，其准确性、可重复性和处理大数据的能力肯定会带来成果。本次系统综述的目的是强调人工智能在检测真菌及其分型方面的实用性，特别关注未来在真菌细胞学中的应用。我们还简要介绍了人工智能的基础知识。