Constructing and Visualizing Models using Mime-based Machine-learning Framework

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Цитируется: 4

06:19 мин.

22 июля 2025 г.

10.3791/68553-v

22 июля 2025 г.

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Hongwei Liu^*¹^,²^,³^,⁴ , Wei Zhang^*¹^,²^,³^,⁴ , Yihao Zhang^*¹^,²^,³^,⁴ , Xuejun Li¹^,²^,³^,⁴ , Siyi Wanggou¹^,²^,³^,⁴

¹Department of Neurosurgery, Xiangya Hospital, Central South University, ²National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, ³Hunan International Scientific and Technological Cooperation Base of Brain Tumor Research, Xiangya Hospital, Central South University, ⁴Furong Laboratory

^* These authors contributed equally

Mime is a flexible computational framework to construct a machine learning-based integration model with elegant performance. Here, we provide a detailed step-by-step procedure for developing predictive models with high accuracy, leveraging complex datasets to identify critical genes associated with disease progression, patient outcomes, and therapeutic response.