دورية أكاديمية

Application of artificial intelligence in endoscopic gastrointestinal tumors

التفاصيل البيبلوغرافية
العنوان: Application of artificial intelligence in endoscopic gastrointestinal tumors
المؤلفون: Yiping Xin, Qi Zhang, Xinyuan Liu, Bingqing Li, Tao Mao, Xiaoyu Li
المصدر: Frontiers in Oncology, Vol 13 (2023)
بيانات النشر: Frontiers Media S.A., 2023.
سنة النشر: 2023
المجموعة: LCC:Neoplasms. Tumors. Oncology. Including cancer and carcinogens
مصطلحات موضوعية: artificial intelligence, deep learning, gastric cancer, colorectal cancer, adenoma detection rate, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
الوصف: With an increasing number of patients with gastrointestinal cancer, effective and accurate early diagnostic clinical tools are required provide better health care for patients with gastrointestinal cancer. Recent studies have shown that artificial intelligence (AI) plays an important role in the diagnosis and treatment of patients with gastrointestinal tumors, which not only improves the efficiency of early tumor screening, but also significantly improves the survival rate of patients after treatment. With the aid of efficient learning and judgment abilities of AI, endoscopists can improve the accuracy of diagnosis and treatment through endoscopy and avoid incorrect descriptions or judgments of gastrointestinal lesions. The present article provides an overview of the application status of various artificial intelligence in gastric and colorectal cancers in recent years, and the direction of future research and clinical practice is clarified from a clinical perspective to provide a comprehensive theoretical basis for AI as a promising diagnostic and therapeutic tool for gastrointestinal cancer
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2234-943X
Relation: https://www.frontiersin.org/articles/10.3389/fonc.2023.1239788/full; https://doaj.org/toc/2234-943X
DOI: 10.3389/fonc.2023.1239788
URL الوصول: https://doaj.org/article/8ba99f427d024d92bc6948bd908283db
رقم الأكسشن: edsdoj.8ba99f427d024d92bc6948bd908283db
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:2234943X
DOI:10.3389/fonc.2023.1239788