Amalgamation of cloud-based colonoscopy videos with patient-level metadata to facilitate large-scale machine learning

Background and study aims  Storage of full-length endoscopic procedures is becoming increasingly popular. To facilitate large-scale machine learning (ML) focused on clinical outcomes, these videos must be merged with the patient-level data in the electronic health record (EHR). Our aim was to presen...

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Detalles Bibliográficos
Autores principales: Keswani, Rajesh N., Byrd, Daniel, Garcia Vicente, Florencia, Heller, J. Alex, Klug, Matthew, Mazumder, Nikhilesh R., Wood, Jordan, Yang, Anthony D., Etemadi, Mozziyar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Georg Thieme Verlag KG 2021
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7857968/
https://www.ncbi.nlm.nih.gov/pubmed/33553586
http://dx.doi.org/10.1055/a-1326-1289

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7857968/
https://www.ncbi.nlm.nih.gov/pubmed/33553586
http://dx.doi.org/10.1055/a-1326-1289

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