A new generation of smart medical technology represented by AI robots is subverting traditional methods of diagnosis and treatment. The Jiangsu Smart Medical Summit Forum, jointly hosted by the Jiangsu Artificial Intelligence Society, the Nanjing Jiangning High-tech Zone Management Committee, and the Jidong Medical Technology Group, was held recently in Jiangning. More than 600 experts and scholars from the national medical big data and artificial intelligence fields have in-depth discussions on the latest developments in smart medical innovation and research and transformation applications.
Liu Lei, chairman of Jidong Group, said that artificial intelligence is bringing revolutionary changes in the field of medical diagnosis. Taking lung cancer as an example, in the past, screening lung nodules relied on doctors to observe one inch and one inch on CT scan images. It was not only a lot of work, but also easy to overlook, and the accuracy rate was only about 65%. Now, through the AI ​​system, one minute. You can watch 15 films, and the accuracy of reading is over 85%. For some complicated films, the "artificial + AI" method can further improve the accuracy of diagnosis. At present, Jidong Medical Technology Group is jointly developing a health management system with the Medical Center of Nanjing Gulou Hospital. This system platform creates a pathway between patients, doctors and hospitals to achieve data on patient health assessment, health management, and post-examination follow-up. Sharing, forming a personal-centric life-cycle health management.
Du Qiang, CEO of Jiangsu Xiaobai Wisdom Medical Co., said that the visual AI system they developed can now automatically identify B-ultrasound, CT, gastroscope, magnetic resonance and other films for eight diseases including liver disease, prostate cancer, lung cancer and thyroid disease. The intelligent assistant diagnosis system has been clinically tested in Zhongshan Hospital of Guangzhou and the Affiliated Hospital of the Fourth Military Medical University. The accuracy of recognition of thyroid diseases is as high as 96%.
The “ AI+Medical †application is inseparable from the information exchange and big data sharing between hospitals. However, one unavoidable fact is that the medical information of most hospitals in China is “islandâ€. According to some surveys, more than 70% of hospitals have achieved medical informatization, but less than 3% of hospitals have achieved data interoperability. "A lot of patients in the hospital after the pathological features, medical records, will generate a large amount of data, but this information can not be shared between hospitals, even in the same hospital between different departments is difficult to share." Liu Lei revealed that because of the hospital The information is not open, resulting in the same patient visiting different hospitals and even in different departments of the same hospital. All the examinations must be done again, which not only causes great losses to the patients, but also causes great waste of medical resources.
Experts also pointed out that the information of a single hospital or several hospitals is not enough to find the common epidemic characteristics of some diseases, but if you collect the massive information of dozens and hundreds of hospitals and conduct big data analysis, you can Discover the prevalence of some diseases and give countermeasures.
The vice president of a top three hospital in Nanjing said that China has proposed medical information construction for several decades. However, due to the lack of relevant standards at the national level, various hospitals lack standard guidance in the process of building information systems. "Just take the hospital HIS (hospital information system), some are developed with Unix system, some are developed by Linux system, not only the data structure is different, the hardware interface is also very different. HIS products are different in different periods, sometimes even up to several Provided by ten different vendors, resulting in data compatibility and information exchange between different systems within the same hospital.
In addition to differences in technical specifications and operating systems, another important cause of the “islanding†of medical information is administrative and interest barriers. Take Nanjing as an example, there are subordinate hospitals, provincial hospitals, municipal hospitals, enterprise hospitals, and private hospitals. The affiliation relationship between different hospitals is complex, and there are also competitions between the contenders and the resources. Therefore, in order to achieve data interconnection, these barriers must first be broken.
"Information interoperability and sharing of data resources are the general trend of the future." Yin Weidong, director of the Nanjing Health Information Center, said that he hopes to gradually break the information barrier between hospital departments and hospitals through the construction of "smart medical care" in Nanjing. The region is linked into a massive medical big data. Through the value mining of massive data, it guides the trend analysis and prevention of diseases in Jiangsu and even the whole country. ( China Jiangsu Net / Zhong Chongshan )
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