{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,29]],"date-time":"2025-12-29T13:03:47Z","timestamp":1767013427133,"version":"3.48.0"},"reference-count":11,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"12","license":[{"start":{"date-parts":[[2025,10,23]],"date-time":"2025-10-23T00:00:00Z","timestamp":1761177600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["lww.com","ovid.com"],"crossmark-restriction":true},"short-container-title":["Clin Transl Gastroenterol","Clinical and Translational Gastroenterology"],"abstract":"<jats:sec>\n                    <jats:title>INTRODUCTION:<\/jats:title>\n                    <jats:p>Esophageal motility disorders (EMDs) are common in clinical practice, with a high symptomatic burden and significant impact on the patients' quality of life. High-resolution esophageal manometry (HREM) is the gold standard for the evaluation of functional esophageal disorders. The Chicago Classification offers a standardized approach to HREM. However, HREM remains a complex procedure, both in data analysis and in accessibility. This study aimed to develop and validate machine learning (ML) models to detect EMDs according to the Chicago Classification.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS:<\/jats:title>\n                    <jats:p>We retrospectively analyzed 618 HREM examinations from 3 centers (Spain and the United States) using 2 recording systems. Labels were assigned by expert consensus as either disorder present or absent for 2 categories: esophagogastric junction outflow disorders and peristalsis disorders. Several ML models were trained and evaluated. ML classifiers were developed using an 80\/20 patient-level stratified split for training\/validation and testing. Model selection was guided by internal evaluation through repeated 10-fold cross-validation. Model performance was assessed by accuracy and area under the receiver-operating characteristic curve (AUC-ROC).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS:<\/jats:title>\n                    <jats:p>The GradientBoostingClassifier model outperformed the remaining ML models with an accuracy of 0.942 \u00b1 0.015 and an AUC-ROC of 0.921 \u00b1 0.041 for identifying disorders of esophagogastric junction outflow. The xGBClassifier model detected disorders of peristalsis with an accuracy of 0.809 \u00b1 0.029 and an AUC-ROC of 0.871 \u00b1 0.027. Performance was consistent across repeated validations, demonstrating model robustness and generalization.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>DISCUSSION:<\/jats:title>\n                    <jats:p>This multicenter, multidevice study demonstrates that ML models can accurately detect EMDs in HREM. Artificial intelligence-driven HREM may improve diagnosis by standardizing interpretation and reducing interobserver variability.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.14309\/ctg.0000000000000941","type":"journal-article","created":{"date-parts":[[2025,10,23]],"date-time":"2025-10-23T16:00:38Z","timestamp":1761235238000},"page":"e00941","update-policy":"https:\/\/doi.org\/10.1097\/lww.0000000000001000","source":"Crossref","is-referenced-by-count":1,"title":["Artificial Intelligence Driven Diagnosis of Motility Patterns in High-Resolution Esophageal Manometry: A Multicentric Multidevice Study"],"prefix":"10.14309","volume":"16","author":[{"given":"Miguel","family":"Mascarenhas","sequence":"first","affiliation":[{"name":"Precision Medicine Unit, Department of Gastroenterology, Centro Hospitalar Universit\u00e1rio S\u00e3o Jo\u00e3o, Porto, Portugal;"},{"name":"WGO Gastroenterology and Hepatology Training Center, Porto, Portugal;"},{"name":"Faculty of Medicine, University of Porto, Portugal, Porto, Portugal;"}]},{"given":"Joana","family":"Mota","sequence":"additional","affiliation":[{"name":"Precision Medicine Unit, Department of Gastroenterology, Centro Hospitalar Universit\u00e1rio S\u00e3o Jo\u00e3o, Porto, Portugal;"},{"name":"WGO Gastroenterology and Hepatology Training Center, Porto, Portugal;"}]},{"given":"Jo\u00e3o","family":"Rala Cordeiro","sequence":"additional","affiliation":[{"name":"Instituto Telecommunications, Instituto Universit\u00e1rio de Lisboa, Lisbon, Portugal;"},{"name":"Department of Information Science and Technology, Instituto Universit\u00e1rio de Lisboa, Lisbon, Portugal;"}]},{"given":"Francisco","family":"Mendes","sequence":"additional","affiliation":[{"name":"Precision Medicine Unit, Department of Gastroenterology, Centro Hospitalar Universit\u00e1rio S\u00e3o Jo\u00e3o, Porto, Portugal;"},{"name":"WGO Gastroenterology and Hepatology Training Center, Porto, Portugal;"},{"name":"Faculty of Medicine, University of Porto, Portugal, Porto, Portugal;"}]},{"given":"Miguel","family":"Martins","sequence":"additional","affiliation":[{"name":"Precision Medicine Unit, Department of Gastroenterology, Centro Hospitalar Universit\u00e1rio S\u00e3o Jo\u00e3o, Porto, Portugal;"},{"name":"WGO Gastroenterology and Hepatology Training Center, Porto, Portugal;"},{"name":"Faculty of Medicine, University of Porto, Portugal, Porto, Portugal;"}]},{"given":"Pedro","family":"Cardoso","sequence":"additional","affiliation":[{"name":"Precision Medicine Unit, Department of Gastroenterology, Centro Hospitalar Universit\u00e1rio S\u00e3o Jo\u00e3o, Porto, Portugal;"},{"name":"WGO Gastroenterology and Hepatology Training Center, Porto, Portugal;"},{"name":"Faculty of Medicine, University of Porto, Portugal, Porto, Portugal;"}]},{"given":"Maria Jo\u00e3o","family":"Almeida","sequence":"additional","affiliation":[{"name":"Precision Medicine Unit, Department of Gastroenterology, Centro Hospitalar Universit\u00e1rio S\u00e3o Jo\u00e3o, Porto, Portugal;"},{"name":"WGO Gastroenterology and Hepatology Training Center, Porto, Portugal;"}]},{"given":"Antonio","family":"Pinto da Costa","sequence":"additional","affiliation":[{"name":"Hospital Universitario Puerta de Hierro-Majadahonda, Madrid, Spain;"}]},{"given":"Ismael","family":"Hajra Martinez","sequence":"additional","affiliation":[{"name":"Hospital Universitario Puerta de Hierro-Majadahonda, Madrid, Spain;"}]},{"given":"Virginia","family":"Matallana Royo","sequence":"additional","affiliation":[{"name":"Hospital Universitario Puerta de Hierro-Majadahonda, Madrid, Spain;"}]},{"given":"Benjamin","family":"Niland","sequence":"additional","affiliation":[{"name":"Division of Gastroenterology, University of South Alabama, College of Medicine, Mobile, Alabama, USA;"}]},{"given":"Jack","family":"Di Palma","sequence":"additional","affiliation":[{"name":"Division of Gastroenterology, University of South Alabama, College of Medicine, Mobile, Alabama, USA;"}]},{"given":"Jo\u00e3o","family":"Ferreira","sequence":"additional","affiliation":[{"name":"Faculty of Engineering of the University of Porto, Porto, Portugal;"}]},{"given":"Guilherme","family":"Macedo","sequence":"additional","affiliation":[{"name":"Precision Medicine Unit, Department of Gastroenterology, Centro Hospitalar Universit\u00e1rio S\u00e3o Jo\u00e3o, Porto, Portugal;"},{"name":"WGO Gastroenterology and Hepatology Training Center, Porto, Portugal;"},{"name":"Faculty of Medicine, University of Porto, Portugal, Porto, Portugal;"}]},{"given":"Cecilio","family":"Santander","sequence":"additional","affiliation":[{"name":"Hospital Universitario La Princesa, Madrid, Spain."}]}],"member":"276","published-online":{"date-parts":[[2025,12]]},"reference":[{"issue":"6","key":"R2-20251229","doi-asserted-by":"crossref","first-page":"1617","DOI":"10.1053\/j.gastro.2021.12.289","article-title":"Esophageal motility disorders: Current approach to diagnostics and therapeutics","volume":"162","author":"Patel","year":"2022","journal-title":"Gastroenterology"},{"issue":"40","key":"R3-20251229","doi-asserted-by":"crossref","first-page":"6794","DOI":"10.3748\/wjg.v27.i40.6794","article-title":"Artificial intelligence in gastroenterology: A state-of-the-art review","volume":"27","author":"Kr\u00f6ner","year":"2021","journal-title":"World J Gastroenterol"},{"issue":"18","key":"R4-20251229","doi-asserted-by":"crossref","first-page":"10116","DOI":"10.3390\/app131810116","article-title":"Unraveling functional dysphagia: A game-changing automated machine-learning diagnostic approach","volume":"13","author":"Zifan","year":"2023","journal-title":"Appl Sci"},{"key":"R5-20251229","doi-asserted-by":"crossref","first-page":"102233","DOI":"10.1016\/j.artmed.2021.102233","article-title":"A multistage machine learning model for diagnosis of esophageal manometry","volume":"124","author":"Kou","year":"2022","journal-title":"Artif Intell 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Sci"},{"issue":"14","key":"R9-20251229","doi-asserted-by":"crossref","first-page":"5227","DOI":"10.3390\/s22145227","article-title":"Automated Chicago Classification for esophageal motility disorder diagnosis using machine learning","volume":"22","author":"SurdeaBlaga","year":"2022","journal-title":"Sensors (Basel)"},{"key":"R10-20251229","doi-asserted-by":"crossref","first-page":"106212","DOI":"10.1016\/j.cmpb.2021.106212","article-title":"Deep learning for tracing esophageal motility function over time","volume":"207","author":"Wang","year":"2021","journal-title":"Comput Methods Programs Biomed"},{"issue":"1","key":"R11-20251229","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1007\/s12559-023-10179-8","article-title":"Interpreting black-box models: A review on explainable artificial intelligence","volume":"16","author":"Hassija","year":"2024","journal-title":"Cogn Comput"},{"issue":"1","key":"R12-20251229","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1038\/s42256-019-0138-9","article-title":"From local explanations to global understanding with explainable AI for trees","volume":"2","author":"Lundberg","year":"2020","journal-title":"Nat Mach Intell"}],"container-title":["Clinical and Translational 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History"}},{"value":"2025-10-09","name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}}]}}