The cure rate of early cancer is over 90%. Early diagnosis and early screening and early screening are especially important for improving cancer cure rate. The breakthrough of artificial intelligence in medical imaging is of great significance for early screening of cancer. The reporter learned from the Xi'an Municipal Health Planning Committee on February 4 that the Tenth AI Image Screening Project, the Fourth Hospital of the City has joined hands with Tencent to set up a joint laboratory for artificial intelligence medical imaging to jointly initiate clinical trials for fundus screening. The city will strengthen the in-depth cooperation with Tencent and enhance the hospital's "Internet +" smart medical application level.
Assisted fundus screening to improve diagnostic accuracy
AI (Artificial Intelligence) is gradually becoming popular from cutting-edge technologies. Tencent Yingying is Tencent's first product to apply artificial intelligence technology to the medical field, and is mainly dedicated to the application of AI to different fields related to medicine. At present, the research direction mainly includes "Tencent AI Image" and "Tencent Vision AI Aid".
On October 31 last year, at the “Internet +†Digital Economy China Bank·Shaanxi Summit in 2017, the Fourth Hospital of our city and Tencent Company established a joint laboratory of artificial intelligence medical imaging to jointly launch clinical trials for fundus screening.
In the past few months, the Fourth Hospital of the city relied on the artificial intelligence technology of image recognition and deep learning of Tencent, and conducted in-depth research and practice on fundus screening work to assist doctors in screening the fundus, which effectively improved the doctor's diagnosis. Degree, so that the majority of patients enjoy the happiness brought by the "Internet +" progress, the city's fourth hospital is also a step in the process of Internet + smart hospital. Through this successful attempt, the city's health planning department and medical institutions realized that Internet artificial intelligence technology has played an important role in assisting medical diagnosis, making up for the shortage of quality medical resources and narrowing the gap in the uneven distribution of medical care.
Support early screening for diseases such as lung cancer
The reporter learned that the diseases supported by Tencent Yingying include early screening for lung cancer, early screening for esophageal cancer, screening for diabetic retinopathy (the fundus sugar network), and early screening for breast cancer.
China's lung cancer morbidity and mortality are higher, and the most effective means of detection is screening. Early diagnosis and early treatment can increase the patient's five-year survival rate to over 80%. Based on Tencent's deep learning technology, Tencent Yingying has studied and analyzed hundreds of thousands of lung CT images. Through accurate positioning of suspicious nodules, and comprehensive and benign and malignant patients, it provides a comprehensive range of lung cancer for doctors. Auxiliary to improve doctors' diagnostic efficiency and accuracy.
China is a country with high incidence of esophageal cancer, but the traditional diagnostic method makes the early detection rate of esophageal cancer less than 10%, and the accuracy of the identification of early esophageal cancer is as high as 90%, which is through millions of endoscopes. The esophageal image is trained and learned to achieve intelligent recognition of early esophageal cancer lesions, which can assist doctors in clinical diagnosis and reduce the rate of missed detection.
Diabetic retinopathy is the fastest-growing cause of blindness, and nearly 110 million people with diabetes in China are at risk. Early detection can treat the disease, but China lacks specialists to detect the disease. Tencent Yingying studied and analyzed hundreds of thousands of diabetic retinopathy staging data to create a smart screening tool for early screening and clinical staging diagnosis.
Breast cancer is one of the most common malignant tumors in women, and its incidence has increased year by year. Tencent Vision uses deep learning techniques to analyze patients' molybdenum target images and help doctors achieve two major functions: finding the location of suspected lesions (including lumps and calcifications); and analyzing the risk of patients having malignant tumors.
Will expand the scope of the auxiliary diagnosis of Tencent
The reporter learned from the Municipal Health Planning Commission that in the next step, the city will continue to strengthen the in-depth cooperation with Tencent.
The cooperation includes four aspects, continue to expand the scope of disease support, and use the fundus sugar network, early lung cancer, esophageal cancer, breast cancer screening and auxiliary diagnosis technology that have matured in Tencent. Medical imaging screening and clinical diagnosis are carried out in high-incidence populations, which effectively improves the accuracy of screening and further enhances the diagnostic effect of hospitals in image diagnosis.
Continue to expand the coverage of medical institutions. Explore the development of Tencent Yingying medical imaging screening and clinical auxiliary diagnosis in municipal hospitals, establish a joint laboratory of artificial intelligence medical imaging, and cooperate on screening and image processing of different diseases.
Try to promote and use imaging and disease screening techniques within the medical consortium to achieve telemedicine- assisted diagnosis and mutual recognition of imaging results.
In promoting the construction of the National Health Medical Big Data Center, we will explore the medical information platform of Tencent Yingying Access Zone, and cooperate specifically on the application of imaging diagnostic technology to further enhance the application level of “Internet +†smart medical treatment in our hospital, and build the whole nation for the next step. The Health and Medical Big Data Center lays a good foundation.
(Source: Xi'an News Network)
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