Cargando…
Machine learning using longitudinal prescription and medical claims for the detection of non-alcoholic steatohepatitis (NASH)
OBJECTIVES: To develop and evaluate machine learning models to detect patients with suspected undiagnosed non-alcoholic steatohepatitis (NASH) for diagnostic screening and clinical management. METHODS: In this retrospective observational non-interventional study using administrative medical claims d...
Autores principales: | Yasar, Ozge, Long, Patrick, Harder, Brett, Marshall, Hanna, Bhasin, Sanjay, Lee, Suyin, Delegge, Mark, Roy, Stephanie, Doyle, Orla, Leavitt, Nadea, Rigg, John |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8968511/ https://www.ncbi.nlm.nih.gov/pubmed/35354641 http://dx.doi.org/10.1136/bmjhci-2021-100510 |
Ejemplares similares
-
Finding undiagnosed patients with hepatitis C infection: an application of artificial intelligence to patient claims data
por: Doyle, Orla M., et al.
Publicado: (2020) -
Finding undiagnosed patients with hepatitis C virus: an application of machine learning to US ambulatory electronic medical records
por: Rigg, John, et al.
Publicado: (2023) -
The role of mitochondrial genomics in patients with non-alcoholic steatohepatitis (NASH)
por: Mehta, Rohini, et al.
Publicado: (2016) -
Pharmaceutical Efficacy of Gypenoside LXXV on Non-Alcoholic Steatohepatitis (NASH)
por: Lee, Jin Ha, et al.
Publicado: (2020) -
Drugs for Non-alcoholic Steatohepatitis (NASH): Quest for the Holy Grail
por: Sharma, Mithun, et al.
Publicado: (2021)