Automated Chicago Classification for Esophageal Motility Disorder Diagnosis Using Machine Learning

The goal of this paper is to provide a Machine Learning-based solution that can be utilized to automate the Chicago Classification algorithm, the state-of-the-art scheme for esophageal motility disease identification. First, the photos were preprocessed by locating the area of interest—the precise i...

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Detalles Bibliográficos
Autores principales: Surdea-Blaga, Teodora, Sebestyen, Gheorghe, Czako, Zoltan, Hangan, Anca, Dumitrascu, Dan Lucian, Ismaiel, Abdulrahman, David, Liliana, Zsigmond, Imre, Chiarioni, Giuseppe, Savarino, Edoardo, Leucuta, Daniel Corneliu, Popa, Stefan Lucian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9323128/
https://www.ncbi.nlm.nih.gov/pubmed/35890906
http://dx.doi.org/10.3390/s22145227

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9323128/
https://www.ncbi.nlm.nih.gov/pubmed/35890906
http://dx.doi.org/10.3390/s22145227

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