Clinical study applying machine learning to detect a rare disease: results and lessons learned

Machine learning has the potential to improve identification of patients for appropriate diagnostic testing and treatment, including those who have rare diseases for which effective treatments are available, such as acute hepatic porphyria (AHP). We trained a machine learning model on 205 571 comple...

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Detalles Bibliográficos
Autores principales: Hersh, William R, Cohen, Aaron M, Nguyen, Michelle M, Bensching, Katherine L, Deloughery, Thomas G
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Brief Communications
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9243401/
https://www.ncbi.nlm.nih.gov/pubmed/35783073
http://dx.doi.org/10.1093/jamiaopen/ooac053

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9243401/
https://www.ncbi.nlm.nih.gov/pubmed/35783073
http://dx.doi.org/10.1093/jamiaopen/ooac053

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