Prediction of tuberculosis using an automated machine learning platform for models trained on synthetic data

High-quality medical data is critical to the development and implementation of machine learning (ML) algorithms in healthcare; however, security, and privacy concerns continue to limit access. We sought to determine the utility of “synthetic data” in training ML algorithms for the detection of tuber...

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Detalles Bibliográficos
Autores principales: Rashidi, Hooman H., Khan, Imran H., Dang, Luke T., Albahra, Samer, Ratan, Ujjwal, Chadderwala, Nihir, To, Wilson, Srinivas, Prathima, Wajda, Jeffery, Tran, Nam K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Original Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8794034/
https://www.ncbi.nlm.nih.gov/pubmed/35136677
http://dx.doi.org/10.4103/jpi.jpi_75_21

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8794034/
https://www.ncbi.nlm.nih.gov/pubmed/35136677
http://dx.doi.org/10.4103/jpi.jpi_75_21

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