AI+ medical market has become a popular outlet. Tencent, Keda Xunfei, and Imagine technology have laid out AI+ medical images. This year, Tencent Yingying landed at the first China Simulation Medicine Conference, using AI auxiliary medical care to promote diagnostic efficiency; Keda Xunfei in medical imaging artificial intelligence In the game, the world record of global lung nodule test was refreshed, with an accuracy rate of 94.1%; Pushitech officially announced the completion of a new round of financing of 300 million yuan. As an important part of the diagnosis and treatment process, medical imaging is an inevitable part of future medical development.
According to the report of "Market Map and Industry Development of Medical Imaging" released by Flint, according to China's overall medical expenditure in the past five years, it is estimated that by 2020, the scale of China's medical imaging market will reach 600 billion to 800 billion yuan. However, with the layout of large companies and the technology of artificial intelligence, the scale of the medical imaging market will have new breakthroughs.
The combination of medical imaging and artificial intelligence is a hot spot in the digital medical industry. The layout of large companies has given AI+ medical images a new breakthrough.
Why are big companies aiming at AI+ images?
Since 2014, the development of AI technology has gradually entered the vertical segmentation field. The medical image layout has been for a long time. The national attention, the lack of hospital AI capabilities and the technical accumulation of large companies have led large companies to aim at AI+ images.
First of all, there are relatively few policy restrictions. At present, electronic medical records have great problems in the clinic, mainly due to cumbersome operations, data interconnection and electronic medical record system, which are difficult to meet the special needs of diseases.
Now 80% to 90% of the data in the medical industry comes from medical imaging and does not involve related interests. With artificial intelligence + medical imaging, the problems in the data can be solved, and the natural government will not limit a lot. Instead, support will be encouraged. Therefore, many large companies use medical imaging as a breakthrough, and there are not many factors due to government restrictions.
Secondly, the lack of top AI capabilities in hospitals requires the assistance of large companies. On the one hand, the medical and intelligent voices of the University of Science and Technology are relatively mature, and the voice technology is relatively mature. The accuracy of universal speech recognition has reached 95%. On the other hand, Alibaba’s The recognition rate of image recognition technology is as high as 99.3%, so the hospital does not have such ability. Therefore, large companies are needed to assist.
The reason why Internet companies are targeting medical imaging is that the hospital has a lot of difficulties in this regard. Internet companies use artificial intelligence to empower medical images. After many confirmations, they can be applied to the medical industry to solve the lack of top-level capabilities of hospitals.
Finally, large companies have made some progress in AI+ imaging. In the diagnosis of medical imaging, it is estimated that more than 200,000 imaging screenings have been completed in the past 17 years; the average detection rate of the University of Science and Technology in lung cancer has reached 94.1. %.
Tencent Yingying mainly uses AI image recognition, big data processing, deep learning and other technologies to cross-border medical integration, which can provide auxiliary screening for early esophageal cancer and other diseases. Tencent's screening for an endoscopy took less than 4 seconds, and the accuracy of early esophageal cancer detection was as high as 90%, which also indicates that Tencent has made some progress in AI+ imaging.
Major companies have laid out the medical industry and promoted the development of artificial intelligence + medical care, and will go further in the future.
Tencent, Ali, Imagine Technology, Science and Technology News, AI+ image layout
In 2008, IBM first proposed the concept of "smart medical", and in recent years, several companies have deployed AI medical technology in major hospitals.
Tencent: In 2017, Tencent's first AI product in the medical field, Tencent Yingying, was mainly used to assist doctors in clinical diagnosis and early screening of diseases. AI is increasingly used in medical applications. Tencent's AI medical imaging technology assists doctors in screening for esophageal cancer, improving accuracy and helping more people solve the disease.
For Tencent, the advantages of WeChat and the integration of medical resources have already been opened up in patients, hospitals, clinics, and doctors' industries. Through the layout of many industries such as registration, consultation, and management, a large number of projects have been completed. The work of the front end of the medical industry, and the landing of Tencent's film, also means that Tencent is sinking itself to the lower end of the industry chain, and then open the front and back industries in the future.
Ali: In 2016, Ali Health invested 225 million yuan in Wanliyun and laid out the medical imaging platform “Doctor Youâ€. Ali Health uses medical imaging as a breakthrough in medical AI, laying a good foundation for innovation and payment of the entire business model. Doctor You is currently working together with the three forces of Ali Health, Alibaba Cloud, and Alibaba's IDST visual computing team.
Ali's layout in the field of medical AI is very deep. From Ali Health Platform, Ant Financial Service to Alibaba Cloud, Taobao has formed a stable business line of medical e-commerce, smart medical, product traceability and health management to provide users with more accurate services. . Ali has laid out and landed a number of medical AI products and services, through the AI+ image as a slit, to enter the lower industrial chain of the medical industry.
HKUST News: In 2015, the University of Science and Technology flew to deploy AI+ medical industry. The core technology of the video-assisted diagnostic system of the University of Science and Technology is based on image recognition and deep learning, combined with medical experts' diagnostic experience and a large amount of sample data to derive the benign and malignant diseases.
For a long time, HKUST has built core technologies related to artificial intelligence such as image recognition, translation, and natural language understanding. These technologies have been applied in the medical field, and in voice electronic medical record products, image-assisted diagnostic systems, and intelligent assistants. Made a good achievement. In addition, the layout of the University of Science and Technology Flight on the AI ​​image means that the technology accumulation has more possibilities for realization.
Imagine technology: At present, it is assumed that the mature small lung nodule recognition system will land early, and more than 200,000 imaging examinations were completed in 2017. It is envisaged that the technology will invest in the development of medical imaging AI products with multiple diseases, and accelerate the application of other AI products outside the lung products.
Imagine that technology is deeply rooted in the field of AI medical imaging. Compared with Tencent Ali and other companies, the company has a deeper industrial layout. Therefore, it has certain advantages. The technology for medical imaging has been laid out since 2015. It has been in medical care for three years. The field of image-assisted diagnosis has gradually become a full-scenario, full-type medical institution service platform in the medical industry. It also illustrates the in-depth study of ideology technology in AI imaging, which has played a role in the industry.
AI+ images, precisely because of the help of artificial intelligence, can solve the problem of large number of image examinations in large hospitals and high pressure on doctors, and provide more efficient image diagnosis.
AI+ image, facing multiple difficulties
The development of the economy has promoted the advancement of artificial intelligence medical standards, but nowadays, various difficulties have followed.
First of all, the lack of compound talents, according to the Ministry of Industry and Information Technology Education Testing Center, China's artificial intelligence talent gap is more than 5 million, the number of talents cultivated by colleges and universities each year is less than 2,000. In terms of a ratio of 1/10, China has less than 200 medical AI talents per year. This is enough to see a serious imbalance between the supply and demand of artificial intelligence talents. There is a serious shortage of artificial intelligence technical talents in the medical field, which has restricted the development of the industry.
Taking the tumor field as an example, the country is strongly encouraging early cancer screening for high-risk populations. Most of the domestic AI+ imaging fields focus on simple image recognition, and composite talents lacking the accumulation of medical data and analysis of image reports are rare.
Secondly, the accuracy of medical data, on the one hand, is the source of data. Nowadays, medical data involves various fields, and it is difficult for each company to obtain data. It is also important to the quality of the data. A large amount of image data has not been digitized, and the degree of data sharing and interoperability between hospitals is low. The development base and long-term optimization of artificial intelligence requires high quality and continuous data.
On the other hand, it is a problem of data structuring. At present, most medical data comes from medical images, and medical image data is still growing year by year, putting pressure on doctors. Despite the addition of artificial intelligence technology, most medical image data is still lacking in standards. The main reason is that the data structure patterns entered in each hospital are different, and it is impossible to form uniform medical data. The standard inconsistency will delay medical artificial intelligence. Development services.
Furthermore, the AI+ medical business model needs to be established. For some medical institutions, the real demand is not only to provide auxiliary diagnostic products, but to complete a full range of diagnostic imaging services. At present, it is not only required for diagnostic service providers to provide artificial intelligence-assisted readings, but also the final diagnosis results of professional imaging doctors, to achieve greater business models and prospects, and to cooperate with enterprises and hospitals to achieve profitability.
Finally, China's medical infrastructure itself is lagging behind. The main driving force for economic growth in some developed countries comes from the medical and health industry. The value added of the health care industry in the United States, Japan and other countries accounts for more than 10% of GDP. However, domestic medical health The industrial added value accounts for less than 5% of GDP. Due to the imperfect domestic public medical management system, problems such as high medical costs, low channels, and low coverage are plaguing consumers.
The backwardness of medical infrastructure has limited the development of smart medical care, so that smart medical applications based on the Internet of Things are not enough to drive industrial development. Although AI technology has been applied to medical imaging, there are only a few clinical applications, and the current level of AI medical treatment is not high, and there are many defects in practical applications.
AI+ images, getting medical data and promoting medical development are key
China has a large population and many medical talents. However, there are few talents for artificial intelligence and medical imaging. The data resources of medical imaging are to be opened up, and the medical industry needs artificial intelligence.
As a result of the increase in compound talents, the use of artificial intelligence in medical imaging has been implemented in various hospitals, which has greatly improved efficiency and helped doctors save a lot of time. However, at present, the intelligent transformation of the medical and health industry relies on the continuous supply of compound talents.
In particular, there are very few talents for AI+ medical imaging. Therefore, relevant companies have also launched corresponding talent training programs to attract more scientists and practitioners with good conditions, strengthen professional construction in the field of artificial intelligence, and cultivate medical care. Artificial intelligence professionals.
Second, to open up the medical data industry resources, in terms of data and structure, the medical and health industry is not enough informationization, and the degree of open sharing of medical data is not high. The domestic medical big data industry has just started, and the medical system is relatively closed. In particular, data entry lacks standards, and standards are not uniform and cannot obtain high-quality, open medical data.
For data and structure, Internet companies use artificial intelligence technology and national policy support to establish a structured knowledge base of diagnostic data, actively encourage social innovation and development of medical services, and promote deep integration of medical services and big data technologies to help hospitals. Get valuable, safe, and continuous data that improves diagnostic accuracy on AI+ images.
Third, to promote the medical market business model, the medical market space is huge, with the addition of artificial intelligence technology, various business models have been tapped, and many giants value the medical imaging equipment market. Domestic equipment has a relatively obvious price advantage and a high market share. The Internet company technology empowers the medical industry and applies artificial intelligence to the application scenarios to drive the advancement of the medical market.
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