Development and Validation of a Machine Learning System to Identify Reflux Events in Esophageal 24-Hour pH/Impedance Studies

INTRODUCTION: Esophageal 24-hour pH/impedance testing is routinely performed to diagnose gastroesophageal reflux disease. Interpretation of these studies is time-intensive for expert physicians and has high inter-reader variability. There are no commercially available machine learning tools to assis...

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Detalles Bibliográficos
Autores principales: Zhou, Margaret J., Zikos, Thomas, Goel, Karan, Goel, Kabir, Gu, Albert, Re, Christopher, Florez Rodriguez, David Jose, Clarke, John O., Garcia, Patricia, Fernandez-Becker, Nielsen, Sonu, Irene, Kamal, Afrin, Sinha, Sidhartha R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10584295/
https://www.ncbi.nlm.nih.gov/pubmed/37578060
http://dx.doi.org/10.14309/ctg.0000000000000634

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10584295/
https://www.ncbi.nlm.nih.gov/pubmed/37578060
http://dx.doi.org/10.14309/ctg.0000000000000634

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