After the AI+medical field’s “national team” has divided the world into three parts, do entrepreneurs still have a chance?

After the keynote speech, a medical big data forum was held. Mr. Yang Hongfei, CEO of Huoshi Zaozao, served as the moderator of the forum and asked questions about key issues of concern to insiders, such as medical data, industry situation, and business model.

1. From April to June 2017, three companies were established, namely: China Healthcare Big Data Co., Ltd., China Healthcare Big Data Technology Development Group Co., Ltd., and China Healthcare Big Data Industry Development Co., Ltd. Some media called it the "three-legged tripod" or "three-way split" of the national team. So after this, do entrepreneurs who want to enter the AI ​​+ medical field still have a chance?

"This is closely linked to the reform of my country's entire economic system and how to understand the role of the government and the market." Dai Tao, deputy director of the Health Science and Technology Development Research Center of the National Health and Family Planning Commission, said that the opinions on comprehensively deepening reform at the Third Plenary Session of the 18th CPC Central Committee clearly pointed out that the market should play a decisive role in resource allocation and the government should play a better role. The so-called role of the government is now called: combining regulation and service. Therefore, "the role of the market is absolutely indispensable in this field, and it is absolutely inseparable from everyone's rich and valuable practice."

He believes that as far as data collection is concerned, from the initial collection in the hospital to the final application, there are market mechanisms involved, so there is room for start-up companies.

Li Tiantian, founder and chairman of Dingxiangyuan, expressed his views from the perspective of data acquisition. He believes that "I believe that on the data supply side, the rights and opportunities of the state team and private companies should be the same, and the scope of policy control should be the same. There should be no distinction between the two."

Second, for medical artificial intelligence, data is the means of production. How can we obtain these means of production continuously? Can we obtain them legally and in compliance with regulations?

Dr. Zhang Jiutian from the Data Collaboration Group of the China Biotechnology Development Center said that the problem of data acquisition is a pain point in all industries and fields. Compared with other countries, domestic data problems are more urgent and policies are relatively lagging. However, data sharing is a major trend.

Dai Tao said there are several problems here.

• Medical data is a resource, so it must have value, and if it has value it can be traded, but the trading rules and pricing methods have not yet been established.

• Medical data is private, and many hospitals tend to be conservative and choose not to release it. How to use data well while protecting patient privacy is something that needs to be explored by enterprises and governments.

• It is difficult to share information not only between institutions, but also between different departments of an institution and between different people in a department. But everyone has the need, and the government is constantly issuing documents. In the end, there needs to be successful practice cases to promote it.

Zhang Jiang, managing director of Ping An Venture Capital, said that first, legislation is needed, second, law enforcement is needed, and third, everyone needs to be guided on what to do.

3. Today, most AI+ medical companies are not making money. Some people may worry that this will be the same as mobile medical care, where they will not make money for a relatively long period of time. Then, will capital or entrepreneurs still have the motivation to participate in it?

"This is a question that any entrepreneurial team should think about every day." Li Tiantian said that he has two different ways of thinking when looking at mobile medical care or artificial intelligence: one is to start with technology, what kind of technology and data do I have now, and what problems can I solve; the other is to start with the scenario, and conversely, I want to commercialize this scenario or close the service loop, and in turn, what mobile medical technology or artificial intelligence data do I need.

Li Tiantian said that Dingxiangyuan took the second path, which is to reverse the application scenarios to find out what kind of technology and platform is needed, which is easier to enter commercialization. But he also admitted that "if we push it out from a purely technical perspective, there may be great value or good application scenarios." The model is also constantly changing, which requires entrepreneurs to have both poetry and distant places, as well as the present situation, and the two should be combined.

Zhang Jiang said, "From our perspective, entrepreneurs lack application scenarios. Entrepreneurs often start from a technical perspective and have advantageous data at hand, but lack large-scale application scenarios. We have application scenarios, but what we lack is technical capabilities." Therefore, he suggested that entrepreneurs play to their strengths.

He gave entrepreneurs some advice: First, make sure you are the best in China in your own field, "then you will have great value and can attack or defend." Second, you must have advantages, at least advantages in some areas, and third, you must be prepared for funding.

"The future is unlimited. Demand is paramount and we should be demand-oriented. Then we should do professional things," said Dai Tao.

Zhang Jiutian believes that application scenarios may also be divided into several levels. If it is driven by scenarios or needs, it is application-oriented, and the risk is that you may be led by the nose; if it is based on feelings and interests, many people are willing to invest money now. "It should be two legs moving forward together, constantly supporting each other." He said that the industry is currently paying more attention to scenarios and applications, but there are many things behind them that deserve everyone's attention.

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