On June 15, 2018, under the guidance of Shanghai Economic and Information Technology Commission, Shanghai Municipal Commission of Commerce, Shanghai Changning District People's Government, Shanghai Changning District Youth Federation and Yiou Company jointly organized "2018 Global Intelligence + New Business The Summit - Smart + Great Health Summit was successfully held at the Shanghai Changning World Trade Center.
This summit is based on AI and medical treatment . It focuses on digital life, smart medical, genetic testing, AI imaging, health management, hospital management and other major themes, and conducts a full and in-depth discussion on AI empowerment. Guests attending the summit included Ma Jun, Dean of Shanghai Tongren Hospital, Kang Rong, Vice President of Microsoft Greater China, Wang Xi, Vice President and Chief Technology Officer of Philips China, and Founder and CEO of Tumar Shenwei, Founder of Voxel Technology Ding Xiaowei, CEO and CEO, Zhang Chunxi, Vice President of Technology Marketing, Li Chaoyang, Vice President of Shenrui Medical Market, Zhao Nan, Co-founder of Jellyfish Gene, and Li Yuxin, Founder of Health and Benefits, Sun Qi, Founding Managing Partner of Dow Investment, and Deputy Director of Yiou Company President Gao, Vice President of Yiou Company and Dean of Yiou Think Tank Institute by Tian Yu.
At the conference, Zhong Ma, founder and CEO of Tuma Shenwei, delivered a keynote speech entitled "Let's Learn Deep into Intelligent Medicine."
The following is a live speech shorthand:
Hello everyone, I am the founder of Tuma Deep and the founder of the company. I am here to be here to share with you some of our company's experience in artificial intelligence medical imaging. I am very honored. The theme of my speech today is to let deep learning enter smart medical care.
Combination of Al and medical
Speaking of smart medical care, there are many applications of smart medical care. We say that prevention of diseases is a very important area. Auxiliary medical treatment is also a very big direction. We do medical image processing, which is a very hot and very large application direction, including our health management, including our diet, daily life habits, which should be placed in the direction of smart medical care.
AI combined with these directions can be applied in multiple scenarios, such as the auxiliary medical research platform, which contains the speech processing, semantic processing, and natural language processing that can be applied in the hospital's EM2 system. This management can be Convenient structured report. For example, health management, nutrition, the energy of each food, its nutrient content can be automatically analyzed by artificial intelligence, and remind us of daily intake. Drug discovery is new and there are drug predictions. Auxiliary clinics, like our company is a company that assists in medical diagnosis and treatment programs. Medical imaging virtual doctor assistants, including nurses in the home, can monitor our daily physiological indicators in real time.
Talk about the development of the international Al medical industry . There are about a hundred companies in the global AI medical company, including more than 90 well-known startups in the world, and 20 or 30 of them are mainly in the direction of medical imaging, analysis and testing. For example, medical insurance companies need to do some analysis on their patients to determine what kind of insurance their patients are suitable for. These risks are very necessary. Besides pathology, we know that many companies, especially in the United States, have a very large and urgent work in the pathological analysis of their digitalization of pathology.
Domestically, we know that the domestic AI medical industry has no fewer than 100 startup companies from 2016 to the present. The main direction of more than 70 companies in more than 100 companies is the analysis of medical images and the labeling of medical data. This direction is considered to be a very direct medical application direction; there is also the direction of radiotherapy, mainly radiology medical imaging. There are also many companies doing research on AI in this area, mainly focusing on the automatic planning of the bull's-eye in the process of radiotherapy and adaptive diagnostic monitoring. This is a very important direction; there are also three-dimensional reconstruction, thinking more about the analysis of medical images. Deep learning and how AI analyzes medical images can also help in imaging. For example, the control of image quality and the choice of algorithms can be realized by deep learning. We know that there are also some companies. Home, including ultrasound images and CT images in many directions.
We have made statistics on these three directions. We found that in domestic AI innovation companies, about 70%-75% of enterprises are doing medical image analysis. This is a very concentrated area, which is relatively scattered with foreign countries. The situation is different. The other 20%, 30% are in the two directions just mentioned.
The value of deep learning in the medical field
First of all, doctors, doctors are the biggest users and our customers. Where is the biggest help for doctors? First, deep learning can help low-grade doctors or doctors in remote areas to quickly upgrade to their seniority. The second is the improvement of work efficiency. Chinese doctors as a group, hospitals as an industry, its productivity is not enough, and our AI can greatly improve the productivity of doctors in this respect.
Let's talk about the patient. By automatic inspection, the AI ​​can report all the diseases of the patient to the doctor in advance, reminding the doctor and the patient to pay attention, so it is submitted to the patient as a precise, efficient and personalized diagnosis and treatment plan. This is hard to achieve without AI.
Let's talk about the hospital and bring the greatest help to the hospital: First, increase efficiency; Second, reduce costs.
Pharmaceutical companies, everyone knows that using artificial intelligence technology to do drug research and development can shorten its research and development cycle. Many oncology drugs have recently learned that there are many emerging companies in China, and there are many in the United States. These companies are using artificial intelligence and machine learning to develop drugs.
Gene sequencing has been developed for about 10 years. In the last six or seven years, this technology has been very mature. This technology uses many methods of machine learning artificial intelligence, especially the method of machine learning. We analyze it by doing statistical methods. A certain type of population is prone to the cause of a certain type of disease, which is achieved by means of large statistics.
For medical insurance companies, each radiotherapy patient needs 10-12 million per year. If you find an early patient through artificial intelligence, you can complete the disease by doing surgery plus radiotherapy for 40,000 dollars a year. Healing, this is the help of medical insurance. At the same time, all the insured patients can be analyzed by big data. Through the analysis of the genes of different patients and his lifestyle, he is not suitable for insurance, and is suitable. Which type of insurance.
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