The JIYING TECHNOLOGY Co.,LTD.'s team participated in the 22nd International Workshop on Campylobacters, Helicobacters, and Related Microorganisms (CHRO 2024) in Australia. |
Dr. Meng Sijun, Vice President of JIYING TECHNOLOGY Co.,LTD., and Mr. Kuang Shaoming, Chief Strategy Officer, attended the 22nd International Conference on Spirochetes and Campylobacters from October 5th to 11th in Australia. During the three-day symposium, the JY Technology team had the privilege of listening to excellent presentations alongside distinguished individuals from various industries, and eagerly awaited the announcement of the 2024 Nobel Prize in the conference room. During the conference, the JJIYING TECHNOLOGY Co.,LTD. 's delegation engaged in in-depth discussions with Professor Barry J. Marshall and his team on the prevention and treatment of global gastrointestinal cancers and infectious diseases, and listened carefully to their valuable opinions and professional guidance. Professor Barry J. Marshall provided support at the exhibition site, and the JIYING TECHNOLOGY Co.,LTD. 's team took the opportunity to introduce their company's product, the Genoimage® Gastrointestinal Early Tumor Auxiliary Screening System, to them in detail.
The Genoimage® Gastrointestinal Early Tumor Auxiliary Screening-Diagnosis-Typing System launched by JIYING TECHNOLOGY Co.,LTD. is a comprehensive solution that integrates multiple advanced artificial intelligence models. This system first allows the general public or medical staff to use a high-risk population screening system based on large language models for early self-examination or rapid triage of potential high-risk individuals. For patients who need gastrointestinal tumor screening, doctors can utilize an endoscopy auxiliary diagnostic system based on multimodal deep learning models to accurately identify and locate precancerous lesions, thereby reducing the rate of missed detections. Additionally, for lesions identified during endoscopic examinations, Genoimage® employs its explainable deep learning model's lesion carcinogenesis risk typing system to assess the risk of malignancy. This suite of intelligent tools greatly enhances the possibility of early detection, early intervention, and early treatment of gastrointestinal tumors.
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