NASHmap: clinical utility of a machine learning model to identify patients at risk of NASH in real-world settings

The NASHmap model is a non-invasive tool using 14 variables (features) collected in standard clinical practice to classify patients as probable nonalcoholic steatohepatitis (NASH) or non-NASH, and here we have explored its performance and prediction accuracy. The National Institute of Diabetes and D...

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Detalles Bibliográficos
Autores principales: Schattenberg, Jörn M., Balp, Maria-Magdalena, Reinhart, Brenda, Tietz, Andreas, Regnier, Stephane A., Capkun, Gorana, Ye, Qin, Loeffler, Jürgen, Pedrosa, Marcos C., Docherty, Matt
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10076319/
https://www.ncbi.nlm.nih.gov/pubmed/37019931
http://dx.doi.org/10.1038/s41598-023-32551-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10076319/
https://www.ncbi.nlm.nih.gov/pubmed/37019931
http://dx.doi.org/10.1038/s41598-023-32551-2

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