Literature DB >> 34739406

Artificial Intelligence in the Diagnosis of Upper Gastrointestinal Diseases.

Pierfrancesco Visaggi1, Nicola de Bortoli1, Brigida Barberio2, Vincenzo Savarino3, Roberto Oleas4, Emma M Rosi1, Santino Marchi1, Mentore Ribolsi5, Edoardo Savarino2.   

Abstract

Artificial intelligence (AI) has enormous potential to support clinical routine workflows and therefore is gaining increasing popularity among medical professionals. In the field of gastroenterology, investigations on AI and computer-aided diagnosis (CAD) systems have mainly focused on the lower gastrointestinal (GI) tract. However, numerous CAD tools have been tested also in upper GI disorders showing encouraging results. The main application of AI in the upper GI tract is endoscopy; however, the need to analyze increasing loads of numerical and categorical data in short times has pushed researchers to investigate applications of AI systems in other upper GI settings, including gastroesophageal reflux disease, eosinophilic esophagitis, and motility disorders. AI and CAD systems will be increasingly incorporated into daily clinical practice in the coming years, thus at least basic notions will be soon required among physicians. For noninsiders, the working principles and potential of AI may be as fascinating as obscure. Accordingly, we reviewed systematic reviews, meta-analyses, randomized controlled trials, and original research articles regarding the performance of AI in the diagnosis of both malignant and benign esophageal and gastric diseases, also discussing essential characteristics of AI.
Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.

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Year:  2022        PMID: 34739406     DOI: 10.1097/MCG.0000000000001629

Source DB:  PubMed          Journal:  J Clin Gastroenterol        ISSN: 0192-0790            Impact factor:   3.062


  4 in total

1.  Advances on Neurogastroenterology and Motility Disorders: Pathophysiology, Diagnostics and Management.

Authors:  Amir Mari; Edoardo Savarino
Journal:  J Clin Med       Date:  2022-05-20       Impact factor: 4.964

Review 2.  Artificial Intelligence for Upper Gastrointestinal Endoscopy: A Roadmap from Technology Development to Clinical Practice.

Authors:  Francesco Renna; Miguel Martins; Alexandre Neto; António Cunha; Diogo Libânio; Mário Dinis-Ribeiro; Miguel Coimbra
Journal:  Diagnostics (Basel)       Date:  2022-05-21

Review 3.  Clinical use of mean nocturnal baseline impedance and post-reflux swallow-induced peristaltic wave index for the diagnosis of gastro-esophageal reflux disease.

Authors:  Pierfrancesco Visaggi; Lucia Mariani; Federica Baiano Svizzero; Luca Tarducci; Andrea Sostilio; Marzio Frazzoni; Salvatore Tolone; Roberto Penagini; Leonardo Frazzoni; Linda Ceccarelli; Vincenzo Savarino; Massimo Bellini; Prakash C Gyawali; Edoardo V Savarino; Nicola de Bortoli
Journal:  Esophagus       Date:  2022-06-29       Impact factor: 3.671

4.  Global research trends of artificial intelligence applied in esophageal carcinoma: A bibliometric analysis (2000-2022) via CiteSpace and VOSviewer.

Authors:  Jia-Xin Tu; Xue-Ting Lin; Hui-Qing Ye; Shan-Lan Yang; Li-Fang Deng; Ruo-Ling Zhu; Lei Wu; Xiao-Qiang Zhang
Journal:  Front Oncol       Date:  2022-08-25       Impact factor: 5.738

  4 in total

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