Identification of spinal tuberculosis subphenotypes using routine clinical data: a study based on unsupervised machine learning

OBJECTIVE: The identification of spinal tuberculosis subphenotypes is an integral component of precision medicine. However, we lack proper study models to identify subphenotypes in patients with spinal tuberculosis. Here we identified possible subphenotypes of spinal tuberculosis and compared their...

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Detalles Bibliográficos
Autores principales: Yao, Yuanlin, Wu, Shaofeng, Liu, Chong, Zhou, Chenxing, Zhu, Jichong, Chen, Tianyou, Huang, Chengqian, Feng, Sitan, Zhang, Bin, Wu, Siling, Ma, Fengzhi, Liu, Lu, Zhan, Xinli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2023
Materias:
Infectious Diseases
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10448834/
https://www.ncbi.nlm.nih.gov/pubmed/37611242
http://dx.doi.org/10.1080/07853890.2023.2249004

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10448834/
https://www.ncbi.nlm.nih.gov/pubmed/37611242
http://dx.doi.org/10.1080/07853890.2023.2249004

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