Cohort-Derived Machine Learning Models for Individual Prediction of Chronic Kidney Disease in People Living With Human Immunodeficiency Virus: A Prospective Multicenter Cohort Study

BACKGROUND: It is unclear whether data-driven machine learning models, which are trained on large epidemiological cohorts, may improve prediction of comorbidities in people living with human immunodeficiency virus (HIV). METHODS: In this proof-of-concept study, we included people living with HIV in...

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Detalles Bibliográficos
Autores principales: Roth, Jan A, Radevski, Gorjan, Marzolini, Catia, Rauch, Andri, Günthard, Huldrych F, Kouyos, Roger D, Fux, Christoph A, Scherrer, Alexandra U, Calmy, Alexandra, Cavassini, Matthias, Kahlert, Christian R, Bernasconi, Enos, Bogojeska, Jasmina, Battegay, Manuel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Major Articles and Brief Reports
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8514185/
https://www.ncbi.nlm.nih.gov/pubmed/32386061
http://dx.doi.org/10.1093/infdis/jiaa236

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8514185/
https://www.ncbi.nlm.nih.gov/pubmed/32386061
http://dx.doi.org/10.1093/infdis/jiaa236

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