Comparison of six machine learning methods.

<div><p>Objective</p><p>The objective of this study was to identify the risk factors that influence metastasis and prognosis in patients with nodular melanoma (NM), as well as to develop and validate a prognostic model using artificial intelligence (AI) algorithms.</p>&...

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Main Author:	Chan Xu (1510759) (author)
Other Authors:	Xiaoyu Yu (719777) (author), Zhendong Ding (1289496) (author), Caixia Fang (19346584) (author), Murong Gao (17438580) (author), Wencai Liu (12058052) (author), Xiaozhu Liu (11459773) (author), Chengliang Yin (7545749) (author), Renjun Gu (483435) (author), Lu Liu (171341) (author), Wenle Li (1234731) (author), Shi-Nan Wu (17815999) (author), Bei Cao (141848) (author)
Published:	2024
Subjects:	Medicine Biotechnology Developmental Biology Cancer Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified year overall survival logistic regression analysis extreme gradient boosting employing multilayer perceptron cox regression analysis assess patient survival model enables clinicians validation results demonstrated ab ), bagging independent prognostic factors prognostic prediction model optimal model among independent risk factors developed prediction model identify risk factors develop metastasis models prognostic factors optimal model risk factors optimal models protective factors end results six models prognosis prediction prognosis model risk level os ), gbm ), 878 ), xlink "> useful supplement system management staging system sequence number retrospectively reviewed primary site nodular melanoma nm ), marital status influence metastasis exclusion criteria effectively reflects clinicopathological characteristics assisted metastasis artificial intelligence app /</ 1 ).
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Comparison of six machine learning methods.

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