Algorithmic prediction of HIV status using nation-wide electronic registry data

BACKGROUND: Late HIV diagnosis is detrimental both to the individual and to society. Strategies to improve early diagnosis of HIV must be a key health care priority. We examined whether nation-wide electronic registry data could be used to predict HIV status using machine learning algorithms. METHOD...

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Detalles Bibliográficos
Autores principales: Ahlström, Magnus G., Ronit, Andreas, Omland, Lars Haukali, Vedel, Søren, Obel, Niels
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Research Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6933258/
https://www.ncbi.nlm.nih.gov/pubmed/31891137
http://dx.doi.org/10.1016/j.eclinm.2019.10.016

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6933258/
https://www.ncbi.nlm.nih.gov/pubmed/31891137
http://dx.doi.org/10.1016/j.eclinm.2019.10.016

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