The DEep learning Framework for pErsonalized dynamic diagnosis of Adverse prognostic ouTcomes in NeuroSyphilis (DEFEAT-NS) study

Jul 19, 2023

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.

Neurosyphilis Sypilis Diagnosis Prognosis Machine learning Deep learning The DEFEAT-NS study
Zhen Lu
Zhen Lu
Biostatistician, Clinical Epidemiologist

Walk with the master

Publications

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