{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T09:09:06Z","timestamp":1767690546879,"version":"3.48.0"},"reference-count":32,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T00:00:00Z","timestamp":1767571200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"abstract":"<jats:p>Background\/Objectives: Functional lumen imaging probe (FLIP) panometry allows real-time assessment of the esophagogastric junction opening and esophageal body contractile activity during an endoscopic procedure. Despite the development of the Dallas Consensus, FLIP panometry analysis remains complex. Artificial intelligence (AI) models have proven their benefit in high-resolution esophageal manometry; however, data on their role in FLIP panometry are scarce. This study aims to develop an AI model for automatic classification of motility patterns during a FLIP panometry exam. Methods: A total of 105 exams from five centers from both the European and American continents were included. Several machine learning models were trained and evaluated for detection of FLIP panometry patterns. Each exam was classified with an expert consensus-based decision according to the Dallas Consensus, with division into a training and testing dataset in a patient-split design. Models\u2019 performance was evaluated through their accuracy and area under the receiver-operating characteristic curve (AUC-ROC). Results: Pathological planimetry patterns were identified by an AdaBoost Classifier with 84.9% accuracy and a mean AUC-ROC of 0.92. Random Forest identified disorders of the esophagogastric junction opening with 86.7% accuracy and an AUC-ROC of 0.973. The Gradient Boosting Classifier identified disorders of the contractile response with 86.0% accuracy and an AUC-ROC of 0.933. Conclusions: In this study, integrating exams with different probe sizes and demographic contexts, a machine learning model accurately classified FLIP panometry exams according to the Dallas Consensus. AI-driven FLIP panometry could revolutionize the approach to this exam during an endoscopic procedure, optimizing exam accuracy, standardization, and accessibility, and transforming patient management.<\/jats:p>","DOI":"10.3390\/jcm15010401","type":"journal-article","created":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T08:42:58Z","timestamp":1767688978000},"page":"401","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Artificial Intelligence and FLIP Panometry\u2014Automated Classification of Esophageal Motility Patterns"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0340-0830","authenticated-orcid":false,"given":"Miguel","family":"Mascarenhas","sequence":"first","affiliation":[{"name":"Gastroenterology Department, Centro Hospitalar Universit\u00e1rio S\u00e3o Jo\u00e3o, 4200-319 Porto, Portugal"},{"name":"Faculdade de Medicina, Universidade do Porto, 4099-002 Porto, Portugal"},{"name":"Department of Gastroenterology, University of South Alabama, Mobile, AL 36688, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5890-7049","authenticated-orcid":false,"given":"Francisco","family":"Mendes","sequence":"additional","affiliation":[{"name":"Gastroenterology Department, Centro Hospitalar Universit\u00e1rio S\u00e3o Jo\u00e3o, 4200-319 Porto, Portugal"},{"name":"Faculdade de Medicina, Universidade do Porto, 4099-002 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6113-1683","authenticated-orcid":false,"given":"Jo\u00e3o","family":"Rala Cordeiro","sequence":"additional","affiliation":[{"name":"Telecomunications Institute, University Institute of Lisbon, 1499-066 Lisbon, Portugal"},{"name":"Department of Information Science and Technology, University Institute of Lisbon, 1499-066 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-3659-8024","authenticated-orcid":false,"given":"Joana","family":"Mota","sequence":"additional","affiliation":[{"name":"Gastroenterology Department, Centro Hospitalar Universit\u00e1rio S\u00e3o Jo\u00e3o, 4200-319 Porto, Portugal"},{"name":"Faculdade de Medicina, Universidade do Porto, 4099-002 Porto, Portugal"}]},{"given":"Miguel","family":"Martins","sequence":"additional","affiliation":[{"name":"Gastroenterology Department, Centro Hospitalar Universit\u00e1rio S\u00e3o Jo\u00e3o, 4200-319 Porto, Portugal"},{"name":"Faculdade de Medicina, Universidade do Porto, 4099-002 Porto, Portugal"}]},{"given":"Maria","family":"Jo\u00e3o Almeida","sequence":"additional","affiliation":[{"name":"Gastroenterology Department, Centro Hospitalar Universit\u00e1rio S\u00e3o Jo\u00e3o, 4200-319 Porto, Portugal"},{"name":"Faculdade de Medicina, Universidade do Porto, 4099-002 Porto, Portugal"}]},{"given":"Catarina","family":"Araujo","sequence":"additional","affiliation":[{"name":"Gastroenterology Department, Centro Hospitalar Universit\u00e1rio S\u00e3o Jo\u00e3o, 4200-319 Porto, Portugal"}]},{"given":"Joana","family":"Frias","sequence":"additional","affiliation":[{"name":"Gastroenterology Department, Centro Hospitalar Universit\u00e1rio S\u00e3o Jo\u00e3o, 4200-319 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9427-5635","authenticated-orcid":false,"given":"Pedro","family":"Cardoso","sequence":"additional","affiliation":[{"name":"Gastroenterology Department, Centro Hospitalar Universit\u00e1rio S\u00e3o Jo\u00e3o, 4200-319 Porto, Portugal"},{"name":"Faculdade de Medicina, Universidade do Porto, 4099-002 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7802-0920","authenticated-orcid":false,"given":"Ismael","family":"El Hajra","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology, Hospital Universitario Puerta de Hierro Majadahonda, 28222 Madrid, Spain"}]},{"given":"Ant\u00f3nio","family":"Pinto da Costa","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology, Hospital Universitario Puerta de Hierro Majadahonda, 28222 Madrid, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7719-0461","authenticated-orcid":false,"given":"Virginia","family":"Matallana","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology, Hospital Universitario Puerta de Hierro Majadahonda, 28222 Madrid, Spain"}]},{"given":"Constanza","family":"Ciriza de Los Rios","sequence":"additional","affiliation":[{"name":"Gastroenterology Department, Hospital Clinico San Carlos, 28040 Madrid, Spain"}]},{"given":"Jo\u00e3o","family":"Ferreira","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Faculdade de Engenharia, Universidade do Porto, 4099-002 Porto, Portugal"}]},{"given":"Miguel","family":"Mascarenhas Saraiva","sequence":"additional","affiliation":[{"name":"ManopH Gastroenterology Clinic, 4000-432 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9387-9872","authenticated-orcid":false,"given":"Guilherme","family":"Macedo","sequence":"additional","affiliation":[{"name":"Gastroenterology Department, Centro Hospitalar Universit\u00e1rio S\u00e3o Jo\u00e3o, 4200-319 Porto, Portugal"},{"name":"Faculdade de Medicina, Universidade do Porto, 4099-002 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-4456-9820","authenticated-orcid":false,"given":"Benjamin","family":"Niland","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology, University of South Alabama, Mobile, AL 36688, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5492-2535","authenticated-orcid":false,"given":"Cecilio","family":"Santander","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology, Hospital Universitario La Princesa, 28006 Madrid, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2026,1,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e14058","DOI":"10.1111\/nmo.14058","article-title":"Esophageal motility disorders on high-resolution manometry: Chicago classification version 4.0\u00a9","volume":"33","author":"Yadlapati","year":"2021","journal-title":"Neurogastroenterol. 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