Sypilis

Non-therapeutic clinical diagnosis system for neurological syphilis based on machine learning
The first inventor (rank 1/1).
Zhen Lu
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Non-therapeutic clinical diagnosis system for neurological syphilis based on machine learning
Diagnosis of neurosyphilis in HIV-negative patients with syphilis: development, validation, and clinical utility of a suite of machine learning models
Background: The ability to accurately identify the absolute risk of neurosyphilis diagnosis for patients with syphilis would allow …
Huachun Zou, Zhen Lu, Wenjia Weng, Ligang Yang, Luoyao Yang, Xinying Leng, Junfeng Wang, Yi-Fan Lin, Jiaxin Wu, Leiwen Fu, Xiaohui Zhang, Yuwei Li, Liuyuan Wang, Xinsheng Wu, Xinyi Zhou, Tian Tian, Lixia Huang, Christina M. Marra, Bin Yang, Tian-Ci Yang, Wujian Ke
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Diagnosis of neurosyphilis in HIV-negative patients with syphilis: development, validation, and clinical utility of a suite of machine learning models
The DEep learning Framework for pErsonalized dynamic diagnosis of Adverse prognostic ouTcomes in NeuroSyphilis (DEFEAT-NS) study
The DEep learning Framework for pErsonalized dynamic diagnosis of Adverse prognostic ouTcomes in NeuroSyphilis (DEFEAT-NS) study is committed to using deep learning and machine learning to achieve accurate diagnosis and better treatment for neurosyphilis patients, and contribute to the health of the people.