Behind the “AI+medical” fire! Use blockchain technology to solve the data bottleneck problem

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In recent years, the popularity of AI technology is very high. Many enterprises are actively studying this technology and actively applying it to traditional fields, such as automobile, medical treatment, security, etc. AI will bring new revolutionary waves to many industries.
Domestic enterprises have laid out “AI+medical” in succession
2017 is called the first year of AI application, and various technologies are gradually landing from concept to industry. In the long run, the AI industry is in an explosive growth stage in terms of technology, industrial investment and enterprises, and gradually begins to penetrate into the vertical industry.
“AI+medical” is becoming the new darling of the capital market, attracting the attention of a large number of investors. From the financing dynamics of domestic AI chip companies in the past two months, security, medical care and driverless driving are the areas of focus in the future, which also reflects the broad prospects of AI+medical from the side.
Behind the “AI+medical” fire! Use blockchain technology to solve the data bottleneck problem
AI medicine is a very imaginative industry. The domestic AI medical upsurge began in the field of medical imaging. The future opportunity is to use AI technology to do drug research and development, even life genetic engineering, etc. The medical market has become a battleground for all AI strategists. For example, domestic chip companies such as Shangtang Technology, Cambrian and Itu Technology are focusing on the medical field through financing.
Behind the “AI+medical” fire
Behind the fire of “AI+medical” is the pain in the domestic traditional medical market. For example, the imbalance between supply and demand of high-quality medical resources, the long training cycle of doctors, the high rate of misdiagnosis, the rapid change of disease spectrum, the rapid change of technology, as well as the intensification of population aging, the growth of chronic diseases, and the improvement of people’s attention to health, have contributed to the development of medical AI.
Since the birth of AI, the theory and technology have become increasingly mature, and the application field has also expanded. Especially in the medical field, AI has a very broad prospect. A large number of medical AI start-ups have sprung up in a centralized manner. Internet giants at home and abroad have actively deployed medical AI, and traditional medical enterprises have introduced AI talents and technologies. In 2018, “AI+medical” became popular.
The bottleneck of “AI+medical” application is data
Despite the rapid development of “AI+medical”, there are many problems. One is that whether AI technology can support basic medical services needs to be verified, and the problem of medical data processing and quality needs to be solved. At present, there are still great problems in the quality of medical data entered manually in hospitals, which also leads to the fact that there are not many medical data that can be applied to AI. Artificial intelligence medicine is still a new thing. Only by solving data and other problems can we truly break through the bottleneck of development.
As for the data bottleneck problem of AI application in medical treatment, Qian Dahong, a professor at the School of Biomedical Engineering of Shanghai Jiaotong University and a national * * * expert, said that for hospitals, data is a valuable asset, and there are security and privacy problems. Centralized data storage cannot solve these two problems.
Some insiders said that compared with automatic driving technology, AI has much less uncontrollability in the medical field. The reason is that the organs and functions of the human body are relatively fixed, not as complex as the road conditions of some roads. With the further development of machine learning technology, it will become a trend for doctors to diagnose and manage patients with artificial intelligence in the future.
Based on the data bottleneck problem of AI in medical application, Qian Dahong, a professor of the School of Biomedical Engineering of Shanghai Jiaotong University and a national * * * * expert, proposed an architecture based on blockchain and distributed security computing, so that the big data required by AI can be safely shared. From August 30 to August 31, it will share its years of research and project experience with you in Shanghai, and make a speech on the theme of “decentralized and safe sharing of medical big data driven by AI-assisted diagnosis and treatment”. At that time, you can go to the scene and discuss with Professor Qian Dahong.
Behind the “AI+medical” fire in 2018! How to use blockchain technology to solve the data bottleneck problem?
OFweek (the second) 2018 AI Industry Conference will be held in Shanghai. At that time, you will deeply discuss AI technology hotspots such as AI chips and AI algorithms with the top AI experts in China, as well as the practical cases of AI implementation in intelligent medicine and other fields. At present, Professor Qian Dahong has confirmed with the organizers to attend the forum. Welcome to the forum to discuss with experts.
Behind the “AI+medical” fire! Use blockchain technology to solve the data bottleneck problem
With the continuous development of AI technology, AI technology will be more fully applied in medical treatment. The experts represented by Professor Qian Dahong solve the data bottleneck problem of AI+medical application through blockchain technology, and believe that AI technology will become more popular in medical treatment in the future, and a new medical model will emerge.
For details and registration, click here to enter
1. From now on to July 31, seize the free seats! All participants who make an appointment to register for the conference can get a free quota of 1500 yuan after being approved by the organizing committee! The number of seats is limited. Make an appointment as soon as possible!
2. In order to support scientific research, scientific research institutes and students can enjoy a 50% discount when registering (the seal of the unit or student certification materials must be issued);
3. For groups with more than 5 participants, please contact the organizing committee directly at+86 - 755 - 83279016 - 2062 or;
4. Due to the large number of participants at the conference site, in order to provide better services for registered visitors, temporary ticket sales are not accepted at all closed meeting sites. Visitors who need to attend the conference should apply in advance. The deadline for registration is August 28. The audience can sign in with the confirmation code and business card when checking in. Audiences who have not registered and registered in advance will not be accepted on site.

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