Comparative analysis of traditional machine learning and automated machine learning: advancing inverted papilloma versus associated squamous cell carcinoma diagnosis.
Farideh Hosseinzadeh, S Saeed Mohammadi, James N Palmer, Michael A Kohanski, Nithin D Adappa, Michael T Chang, Peter H Hwang, Jayakar V Nayak, Zara M Patel
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引用次数: 0
Abstract
Key points: Inverted papilloma conversion to squamous cell carcinoma is not always easy to predict. AutoML requires much less technical knowledge and skill to use than traditional ML. AutoML surpassed the traditional ML algorithm in differentiating IP from IP-SCC.
期刊介绍：
International Forum of Allergy & Rhinologyis a peer-reviewed scientific journal, and the Official Journal of the American Rhinologic Society and the American Academy of Otolaryngic Allergy.
International Forum of Allergy Rhinology provides a forum for clinical researchers, basic scientists, clinicians, and others to publish original research and explore controversies in the medical and surgical treatment of patients with otolaryngic allergy, rhinologic, and skull base conditions. The application of current research to the management of otolaryngic allergy, rhinologic, and skull base diseases and the need for further investigation will be highlighted.
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