Through voice communication, the robot can help patients with guidance; After reading the image data, the machine can issue a diagnosis report… With the progress of science and technology, artificial intelligence (AI) medicine has gradually changed from cutting-edge technology to practical application.

However, the reporter of economic information daily learned that in the process of rapid development, China’s medical artificial intelligence is facing three development difficulties: technical problems need to be broken through, the access threshold needs to be clarified by the regulators, and the business model needs to be established. In this regard, experts suggest that the state should take the lead in database construction, break data barriers, realize medical data sharing, formulate standards as soon as possible, and promote the gathering of high-end talents, so as to achieve an all-round breakthrough.

The second is to reconstruct the medical service model, change “treatment” to “prevention”, and change the passive medical treatment to health service anytime and anywhere. Experts believe that artificial intelligence can efficiently and accurately integrate medical test data, let patients have their own electronic health files and form health big data. Through the monitoring of intelligent mobile terminals and wearable devices, medical institutions and their medical staff can actively find individuals and people with abnormal health status and give health risk tips, health improvement or medical measures in advance.

Some development difficulties encountered by medical artificial intelligence

Medical artificial intelligence can also summarize the laws of disease prevention, diagnosis, treatment and rehabilitation from the dual perspectives of groups and individuals through the analysis, sorting and induction of intelligent tools.

Industry insiders believe that China is expected to rely on these advantages to achieve “corner overtaking” in the field of medical artificial intelligence. At the same time, with the gradual transformation of artificial intelligence from cutting-edge technology to practical application, it may bring significant changes to the current medical pattern. The reporter of economic information daily found that at present, China’s artificial intelligence medical treatment still faces technical problems. It is understood that massive big data and computing power are essential elements for the development of artificial intelligence, especially in medical data sharing. At present, China urgently needs to make up for its shortcomings.

The phenomenon of “data island” is not unified with the data standard, which makes it difficult to share medical data. The accuracy of artificial intelligence needs to learn a lot of data. Experts believe that our country has great advantages in the number of hospital cases. However, due to the lack of sharing of medical data, there is an “island” phenomenon, which is not conducive to the development of artificial intelligence technology. Experts said that taking CT screening of pulmonary nodules as an example, at present, the diagnostic accuracy of medical artificial intelligence products in scenarios such as pulmonary nodules and glycoreticulosis examination in the industry is generally high, but enterprises usually have their own database when training their own models, and their respective algorithms are trained according to their own data, and then use their own data to verify the accuracy. From the regulatory perspective, artificial intelligence has just been applied to the field of medical and health care, some regulatory policies need to be clarified, talent accumulation is still insufficient, and a sustainable business model needs to be established.

According to the classification provisions in the classification catalogue of medical devices issued by the State Drug Administration in 2017, if the diagnostic software provides diagnostic suggestions through algorithms and only auxiliary diagnostic functions do not directly give diagnostic conclusions, it shall apply for certification according to class II medical devices; If the lesion site is automatically identified and clear diagnosis prompt is provided, clinical verification management must be carried out according to class III medical devices. According to insiders, at present, some state-owned enterprises have applied for class II certificates, but the products applying for class III instruments have not been certified.

The industry generally believes that from the aspects of technology, business model and policy, the future development opportunities and challenges of medical artificial intelligence coexist. After the “fire starts a prairie fire”, it still needs a stable model and a rational market to verify. In this regard, Xia Huimin, director of Guangzhou Women’s and children’s Medical Center, Yu Shihui, chief scientific officer of Guangzhou Jinyu Medical Laboratory Group Co., Ltd., and other experts suggested:

Clarify the legal standards for the clinical application of medical artificial intelligence diagnosis. As for “whether the subject of artificial intelligence diagnosis is a doctor or a medical device in law”, the industry suggests that at present, medical imaging artificial intelligence has entered a key stage of development, and its top priority is to do a good job in standard construction and improve relevant policies. According to the experience of the United States, medical imaging products, for example, are used to detect physical conditions and evaluate diseases. The former belongs to class II devices, while the latter belongs to class III devices with higher risk level. At present, most of the medical imaging AI products approved by the U.S. Food and drug administration are classified as class II equipment. We have accumulated a lot of experience in the approval of such equipment, and can provide corresponding approval standards.

Some development difficulties encountered by medical artificial intelligence

It is suggested to promote the gathering of high-end talents through government enterprise cooperation. In 2017, the Ministry of science and technology announced the list of the first batch of national artificial intelligence open innovation platforms. Baidu, Alibaba cloud, Tencent and iFLYTEK were shortlisted. Enterprises deeply participate in interdisciplinary research, which will gather a large number of talent resources for the development of national artificial intelligence and further promote industry university research cooperation. Experts believe that China is likely to achieve world-class results in technologies such as automatic driving and speech recognition, and is expected to integrate research talents in these fields and deeply participate in medical artificial intelligence.

Give full play to the existing advantages and graft algorithm to realize “overtaking in curve”. Xia Huimin suggested that Chinese enterprises should take advantage of the advantages of big data development and make use of the existing international sharing platform to introduce, digest, absorb and innovate. For example, through the new algorithm developed on Google platform and “migration learning”, they can reach or even surpass the international advanced level in some projects in a short time, And form a large-scale comprehensive advantage from point to area.

In recent years, the integration of artificial intelligence technology and the field of medical and health care has deepened. Taking the United States, which has developed the most rapidly in artificial intelligence medical care, as an example, technology giants and capital giants are actively layout the intelligent medical industry, and a large number of start-ups focusing on subdivided fields are also ready to go.

IBM, Google, Microsoft and other technology giants have been laying out artificial intelligence medical services in recent years. For example, IBM Watson can quickly screen cancer patient records and provide doctors with alternative evidence-based treatment options; Google is making efforts in the research of diabetes, neurologic diseases and medical devices. Google deepmind and the British national health system (NHS) work together to develop new technologies. Microsoft has released a personal health management platform to integrate the data collected by different health and fitness devices. Apple, Facebook and other companies have gradually stepped into the medical and health industry by setting up medical and health departments, developing medical and health applications and acquiring medical and health start-ups.

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