echemi logo
Product
  • Product
  • Supplier
  • Inquiry
    Home > Active Ingredient News > Antitumor Therapy > JAMA Network Open: Chinese scientists have developed a new deep learning technique that promises to successfully predict hidden peritometrial metastasis in patients with stomach cancer!

    JAMA Network Open: Chinese scientists have developed a new deep learning technique that promises to successfully predict hidden peritometrial metastasis in patients with stomach cancer!

    • Last Update: 2021-03-06
    • Source: Internet
    • Author: User
    Search more information of high quality chemicals, good prices and reliable suppliers, visit www.echemi.com
    January 11, 2021 // -- Stomach cancer is a common gastrointestinal malignancies that often occur in most patients with advanced stomach cancer, which is considered an invasive cancer and often has a poor prognosis.
    patients with peritina metastasis for stomach cancer are generally not suitable for root-and-drug surgery;
    recently, scientists from the Shenzhen Institute of Advanced Technology of the Chinese Academy of Sciences and others published a study in the international journal JAMA Network Open entitled "Noninvasive Prediction of Occult Peritoneal Metastasis in GasTric Using Deep Learning" Research has developed a deep learning technique to help predict hidden peritioral metastasis in patients with stomach cancer, and in this article, researchers offer a new and non-invasive way to diagnose gastric cancer patients, with the results promising to help develop individualized surgical treatments for gastric cancer patients.
    Photo Source: Chinese Academy of Sciences researcher Xie Yaoqin says the deep learning model we developed, called the Peritoneal Metastasis Network, could use preoperative computer fault scanning (CT) images in patients with stomach cancer to predict their clinically hidden peritoneum metastasis.
    , co-author of this paper, explains that this deep learning model may serve as a reliable non-invasive tool for early diagnosis of clinically early-stage hidden peritometrial metastasis patients.
    , the researchers said the findings of this paper may help us develop new types of individualized preoperative treatment decisions and may avoid unnecessary surgery and patient complications.
    later this year, researchers will continue to conduct more in-depth studies to optimize current learning models to more effectively predict peritometrial metastasis in patients with stomach cancer.
    () original source: Yuming Jiang et al. Noninvasive Prediction of Occult Peritoneal Metastasis in Gastric Cancer Using Deep Learning. JAMA Netw Open. 2021; 4(1):e2032269. DOI: 10.1001/jamanetworkopen.2020.32269
    This article is an English version of an article which is originally in the Chinese language on echemi.com and is provided for information purposes only. This website makes no representation or warranty of any kind, either expressed or implied, as to the accuracy, completeness ownership or reliability of the article or any translations thereof. If you have any concerns or complaints relating to the article, please send an email, providing a detailed description of the concern or complaint, to service@echemi.com. A staff member will contact you within 5 working days. Once verified, infringing content will be removed immediately.

    Contact Us

    The source of this page with content of products and services is from Internet, which doesn't represent ECHEMI's opinion. If you have any queries, please write to service@echemi.com. It will be replied within 5 days.

    Moreover, if you find any instances of plagiarism from the page, please send email to service@echemi.com with relevant evidence.