{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T18:01:12Z","timestamp":1775325672876,"version":"3.50.1"},"reference-count":24,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T00:00:00Z","timestamp":1657670400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Entrepreneurial competences and excellence research in doctoral and postdoctoral programs-ANTREDOC, European Social Fund financing agreement","award":["56437\/24"],"award-info":[{"award-number":["56437\/24"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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\u2014the precise instant of swallowing. After resizing and rescaling the photos, they were utilized as input for the Deep Learning models. The InceptionV3 Deep Learning model was used to identify the precise class of the IRP. We used the DenseNet201 CNN architecture to classify the images into 5 different classes of swallowing disorders. Finally, we combined the results of the two trained ML models to automate the Chicago Classification algorithm. With this solution we obtained a top-1 accuracy and f1-score of 86% with no human intervention, automating the whole flow, from image preprocessing until Chicago classification and diagnosis.<\/jats:p>","DOI":"10.3390\/s22145227","type":"journal-article","created":{"date-parts":[[2022,7,14]],"date-time":"2022-07-14T00:12:40Z","timestamp":1657757560000},"page":"5227","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Automated Chicago Classification for Esophageal Motility Disorder Diagnosis Using Machine Learning"],"prefix":"10.3390","volume":"22","author":[{"given":"Teodora","family":"Surdea-Blaga","sequence":"first","affiliation":[{"name":"Second Medical Department, \u201cIuliu Hatieganu\u201d University of Medicine and Pharmacy, 400006 Cluj-Napoca, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7773-1077","authenticated-orcid":false,"given":"Gheorghe","family":"Sebestyen","sequence":"additional","affiliation":[{"name":"Computer Science Department, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7497-0251","authenticated-orcid":false,"given":"Zoltan","family":"Czako","sequence":"additional","affiliation":[{"name":"Computer Science Department, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4116-694X","authenticated-orcid":false,"given":"Anca","family":"Hangan","sequence":"additional","affiliation":[{"name":"Computer Science Department, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dan Lucian","family":"Dumitrascu","sequence":"additional","affiliation":[{"name":"Second Medical Department, \u201cIuliu Hatieganu\u201d University of Medicine and Pharmacy, 400006 Cluj-Napoca, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7435-271X","authenticated-orcid":false,"given":"Abdulrahman","family":"Ismaiel","sequence":"additional","affiliation":[{"name":"Second Medical Department, \u201cIuliu Hatieganu\u201d University of Medicine and Pharmacy, 400006 Cluj-Napoca, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liliana","family":"David","sequence":"additional","affiliation":[{"name":"Second Medical Department, \u201cIuliu Hatieganu\u201d University of Medicine and Pharmacy, 400006 Cluj-Napoca, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Imre","family":"Zsigmond","sequence":"additional","affiliation":[{"name":"Faculty of Mathematics and Computer Science, Babes-Bolyai University, 400347 Cluj-Napoca, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Giuseppe","family":"Chiarioni","sequence":"additional","affiliation":[{"name":"Division of Gastroenterology, AOUI Verona, University of Verona, 37134 Verona, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3187-2894","authenticated-orcid":false,"given":"Edoardo","family":"Savarino","sequence":"additional","affiliation":[{"name":"Gastroenterology Unit, Department of Surgery, Oncology and Gastroenterology, University of Padua, 35122 Padova, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4218-8622","authenticated-orcid":false,"given":"Daniel Corneliu","family":"Leucuta","sequence":"additional","affiliation":[{"name":"Department of Medical Informatics and Biostatistics, \u201cIuliu Hatieganu\u201d University of Medicine and Pharmacy, 400349 Cluj-Napoca, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5508-2598","authenticated-orcid":false,"given":"Stefan Lucian","family":"Popa","sequence":"additional","affiliation":[{"name":"Second Medical Department, \u201cIuliu Hatieganu\u201d University of Medicine and Pharmacy, 400006 Cluj-Napoca, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"796","DOI":"10.1111\/j.1365-2982.2009.01311.x","article-title":"High-resolution manometry in clinical practice: Utilizing pressure topography to classify oesophageal motility abnormalities","volume":"21","author":"Pandolfino","year":"2009","journal-title":"Neurogastroenterol. 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