دورية أكاديمية
أعرض في EDS

The Impact of Artificial Intelligence in the Endoscopic Assessment of Premalignant and Malignant Esophageal Lesions: Present and Future.

التفاصيل البيبلوغرافية
العنوان: The Impact of Artificial Intelligence in the Endoscopic Assessment of Premalignant and Malignant Esophageal Lesions: Present and Future.
المؤلفون: Lazăr DC; Department V of Internal Medicine I, Discipline of Internal Medicine IV, 'Victor Babeș' University of Medicine and Pharmacy Timișoara, Romania, Eftimie Murgu Sq. no. 2, 300041 Timișoara, Romania., Avram MF; Department of Surgery X, 1st Surgery Discipline, 'Victor Babeș' University of Medicine and Pharmacy Timișoara, Romania, Eftimie Murgu Sq. no. 2, 300041 Timișoara, Romania., Faur AC; Department I, Discipline of Anatomy and Embriology, 'Victor Babeș' University of Medicine and Pharmacy Timișoara, Romania, Eftimie Murgu Sq. no. 2, 300041 Timișoara, Romania., Goldiş A; Department VII of Internal Medicine II, Discipline of Gastroenterology and Hepatology, 'Victor Babeș' University of Medicine and Pharmacy Timișoara, Romania, Eftimie Murgu Sq. no. 2, 300041 Timișoara, Romania., Romoşan I; Department V of Internal Medicine I, Discipline of Internal Medicine IV, 'Victor Babeș' University of Medicine and Pharmacy Timișoara, Romania, Eftimie Murgu Sq. no. 2, 300041 Timișoara, Romania., Tăban S; Department II of Microscopic Morphology, Discipline of Pathology, 'Victor Babeș' University of Medicine and Pharmacy Timișoara, Romania, Eftimie Murgu Sq. no. 2, 300041 Timișoara, Romania., Cornianu M; Department II of Microscopic Morphology, Discipline of Pathology, 'Victor Babeș' University of Medicine and Pharmacy Timișoara, Romania, Eftimie Murgu Sq. no. 2, 300041 Timișoara, Romania.
المصدر: Medicina (Kaunas, Lithuania) [Medicina (Kaunas)] 2020 Jul 21; Vol. 56 (7). Date of Electronic Publication: 2020 Jul 21.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: MDPI Country of Publication: Switzerland NLM ID: 9425208 Publication Model: Electronic Cited Medium: Internet ISSN: 1648-9144 (Electronic) Linking ISSN: 1010660X NLM ISO Abbreviation: Medicina (Kaunas) Subsets: MEDLINE
أسماء مطبوعة: Publication: 2018- : Basel, Switzerland : MDPI
Original Publication: Kaunas : Lietuvos gydytojų sąjunga
مواضيع طبية MeSH: Artificial Intelligence/*standards , Diagnosis, Computer-Assisted/*standards , Esophageal Neoplasms/*diagnosis , Esophagus/*abnormalities , Esophagus/*diagnostic imaging , Mass Screening/*standards, Artificial Intelligence/trends ; Diagnosis, Computer-Assisted/methods ; Diagnosis, Computer-Assisted/statistics & numerical data ; Early Detection of Cancer ; Endoscopy/methods ; Endoscopy/standards ; Humans ; Mass Screening/methods ; Mass Screening/statistics & numerical data ; Prognosis
مستخلص: In the gastroenterology field, the impact of artificial intelligence was investigated for the purposes of diagnostics, risk stratification of patients, improvement in quality of endoscopic procedures and early detection of neoplastic diseases, implementation of the best treatment strategy, and optimization of patient prognosis. Computer-assisted diagnostic systems to evaluate upper endoscopy images have recently emerged as a supporting tool in endoscopy due to the risks of misdiagnosis related to standard endoscopy and different expertise levels of endoscopists, time-consuming procedures, lack of availability of advanced procedures, increasing workloads, and development of endoscopic mass screening programs. Recent research has tended toward computerized, automatic, and real-time detection of lesions, which are approaches that offer utility in daily practice. Despite promising results, certain studies might overexaggerate the diagnostic accuracy of artificial systems, and several limitations remain to be overcome in the future. Therefore, additional multicenter randomized trials and the development of existent database platforms are needed to certify clinical implementation. This paper presents an overview of the literature and the current knowledge of the usefulness of different types of machine learning systems in the assessment of premalignant and malignant esophageal lesions via conventional and advanced endoscopic procedures. This study makes a presentation of the artificial intelligence terminology and refers also to the most prominent recent research on computer-assisted diagnosis of neoplasia on Barrett's esophagus and early esophageal squamous cell carcinoma, and prediction of invasion depth in esophageal neoplasms. Furthermore, this review highlights the main directions of future doctor-computer collaborations in which machines are expected to improve the quality of medical action and routine clinical workflow, thus reducing the burden on physicians.
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فهرسة مساهمة: Keywords: Barrett’s esophagus; artificial intelligence; computer-assisted diagnosis; endoscopy; esophageal cancer
تواريخ الأحداث: Date Created: 20200726 Date Completed: 20210316 Latest Revision: 20210316
رمز التحديث: 20221213
مُعرف محوري في PubMed: PMC7404688
DOI: 10.3390/medicina56070364
PMID: 32708343
قاعدة البيانات: MEDLINE
الوصف
تدمد:1648-9144
DOI:10.3390/medicina56070364