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

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 present...

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Bibliographic Details
Main Authors: Rajesh N. Keswani, Daniel Byrd, Florencia Garcia Vicente, J. Alex Heller, Matthew Klug, Nikhilesh R. Mazumder, Jordan Wood, Anthony D. Yang, Mozziyar Etemadi
Format: Article
Language:English
Published: Georg Thieme Verlag KG 2021-02-01
Series:Endoscopy International Open
Online Access:http://www.thieme-connect.de/DOI/DOI?10.1055/a-1326-1289

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http://www.thieme-connect.de/DOI/DOI?10.1055/a-1326-1289

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