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Application of artificial intelligence in endoscopic gastrointestinal tumors.
Xin, Yiping; Zhang, Qi; Liu, Xinyuan; Li, Bingqing; Mao, Tao; Li, Xiaoyu.
Afiliación
  • Xin Y; Department of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Zhang Q; Department of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Liu X; Department of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Li B; Department of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Mao T; Department of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Li X; Department of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao, China.
Front Oncol ; 13: 1239788, 2023.
Article en En | MEDLINE | ID: mdl-38144533
ABSTRACT
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Oncol Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Oncol Año: 2023 Tipo del documento: Article País de afiliación: China