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Applications of Artificial Intelligence for the Diagnosis of Gastrointestinal Diseases.
Pecere, Silvia; Milluzzo, Sebastian Manuel; Esposito, Gianluca; Dilaghi, Emanuele; Telese, Andrea; Eusebi, Leonardo Henry.
Afiliação
  • Pecere S; Digestive Endoscopy Unit, Fondazione Policlinico Universitario A. Gemelli IRCCS, Università Cattolica del Sacro Cuore, 00135 Rome, Italy.
  • Milluzzo SM; Center for Endoscopic Research Therapeutics and Training (CERTT), Catholic University, 00168 Rome, Italy.
  • Esposito G; Digestive Endoscopy Unit, Fondazione Policlinico Universitario A. Gemelli IRCCS, Università Cattolica del Sacro Cuore, 00135 Rome, Italy.
  • Dilaghi E; Fondazione Poliambulanza Istituto Ospedaliero, 25121 Brescia, Italy.
  • Telese A; Department of Medical-Surgical Sciences and Translational Medicine, Sant'Andrea Hospital, Sapienza University of Rome, 00168 Rome, Italy.
  • Eusebi LH; Department of Medical-Surgical Sciences and Translational Medicine, Sant'Andrea Hospital, Sapienza University of Rome, 00168 Rome, Italy.
Diagnostics (Basel) ; 11(9)2021 Aug 30.
Article em En | MEDLINE | ID: mdl-34573917
ABSTRACT
The development of convolutional neural networks has achieved impressive advances of machine learning in recent years, leading to an increasing use of artificial intelligence (AI) in the field of gastrointestinal (GI) diseases. AI networks have been trained to differentiate benign from malignant lesions, analyze endoscopic and radiological GI images, and assess histological diagnoses, obtaining excellent results and high overall diagnostic accuracy. Nevertheless, there data are lacking on side effects of AI in the gastroenterology field, and high-quality studies comparing the performance of AI networks to health care professionals are still limited. Thus, large, controlled trials in real-time clinical settings are warranted to assess the role of AI in daily clinical practice. This narrative review gives an overview of some of the most relevant potential applications of AI for gastrointestinal diseases, highlighting advantages and main limitations and providing considerations for future development.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article