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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...
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 |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
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 |
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