As a topic related to the vital interests of the general public, medical care has always been an issue of people’s livelihood that the society attaches great importance and attention to. The implementation of relevant government policies and the continuous reform of the medical industry have all been discussed and researched around the public’s medical and health issues, but No matter how thorough the consideration, due to the current medical environment, there are still many difficulties that we cannot consider and solve.
Especially with the increasing population aging and the extremely unbalanced medical resources, how to solve the medical and health problems of the huge and aging population in the future will become a huge pressure and burden on the country's medical care.
The aging population brings a serious shortage of medical resources
According to data as of the end of 2016, China’s elderly population of 60 years and over exceeds 230 million, accounting for 16.7% of the total population. It is estimated that by 2050, China’s elderly population will reach 480 million, accounting for a quarter of the global elderly population. Now that the combined population of the three countries of the United States, Britain and Germany is even larger, the issue of aging will become a new challenge for China's social and economic development and transformation.
At the same time, there are huge challenges in solving the medical and health problems of the huge elderly population. Looking at the current domestic medical environment, the imbalance in the distribution of urban and rural medical resources, the serious lack of medical staff and the huge gap in professionalism have brought huge pressure on national medical resources to a large extent. Therefore, the urgent need for medical resources Under demand, there is an urgent need for a reliable and comprehensive solution to the lack of medical resources.
Just with the rapid development of artificial intelligence, it has achieved very good performance and more successful landing projects in various industries. In particular, the achievements in empowering medical care have given the public hope. Many people in the industry have turned to research on smart medical care, hoping to make a big breakthrough in smart medical care.
AI medical treatment effectively relieves the pressure of insufficient medical resources
At present, artificial intelligence is roughly divided into three stages, weak artificial intelligence, strong artificial intelligence, and super strong artificial intelligence. At present, we are in the era of weak artificial intelligence, that is, artificial intelligence can be stronger than the ability in a certain aspect or a specific field. Humans, but humans are better than artificial intelligence in terms of comprehensive capabilities.
The same is true for AI medical care. We are currently in the stage of weak AI medical care. Simply put, the current AI medical application scenarios are only suitable for a simple link or a certain repetitive and fixed process and work in the medical industry. However, artificial intelligence cannot complete the links such as clinical diagnosis and medical research that require in-depth and flexible brain use.
For example, the AI ​​medical industry research report released by the Sutu Research Institute in the first half of 2018 clearly shows that the current application scenarios of AI medical are mainly applicable to virtual assistants, drug mining, medical imaging, health management, auxiliary diagnosis and treatment, hospital management, disease risk prediction As well as supporting medical research reports and other aspects. At present, the hottest AI medical applications are medical imaging and disease risk prediction.
Although it is currently in the stage of weak AI medical treatment, it can to a large extent alleviate the pressure of serious shortage of medical resources caused by the aging of the population. For example, AI assists doctors in reading CT after deep learning through a large amount of medical data. Imaging and early cancer screening will greatly relieve the pressure of insufficient medical staff and the pressure of misdiagnosis and misjudgment.
In fact, the Internet giant BAT has already solved these problems. In July 2017, Alibaba Health and Wanliyun released the medical artificial intelligence system "Doctor You", which can read 9,000 CT images in half an hour. It can be said that the efficiency is human. Thousands of times. In August 2017, Tencent released the AI ​​medical imaging product "Tencent Miying", which uses artificial intelligence medical imaging technology to assist doctors in early screening for esophageal cancer.
Similarly, Baidu Research Institute also released an AI algorithm called "Neural Condition Random Field" in June this year. It has powerful tumor pathological slice detection capabilities, which will provide important assistance for cancer diagnosis and treatment, and its detection accuracy is even Overtake professional pathologists and break the previous record.
AI medical care still has many barriers that need to be broken through
Although AI medical treatment has achieved substantial results and breakthroughs to a certain extent, due to the technical limitations of AI itself and the impact of the overall environment, AI has not reached a perfect state in enabling medical treatment, and there are still many things that cannot be broken through. barrier.
For example, the "2018 China Medical Artificial Intelligence Development Research Report" released by the Yiou Think Tank stated that there are four major challenges in the development of AI medical care:
One is the problem of data quantity: the overall amount of data in China's medical care is large, but the amount and quality of data for different diseases are uneven, and training data for some diseases is lacking; the problem of health big data islands has been alleviated, but it has not yet reached the depth The stage of learning.
The second is the problem of data quality: the accuracy of labeling in AI data processing is related to the accuracy of the results, and a large number of doctors are still required to label in the past two years. The quality of data in drug research and development is critical to the improvement of research and development efficiency.
The third is the problem of talents: AI algorithm talents and medical talents have different knowledge systems. How to integrate their respective advantages to maximize value is worth thinking about.
The fourth is the market problem: medical care is considered to be the first field of artificial intelligence, but the particularity of medical care will have higher requirements for products, from the recognition of acceptance to the improvement of the corresponding payment system and the access to medical insurance. It takes a long process.
Write to the end
No matter how many barriers AI medical care cannot break through, in short, if we return to the topic, in a sense, AI medical care has largely solved the pressure of serious shortage of medical resources caused by artificial aging.
On the other hand, the huge market value of AI medical care in the future drives giant companies and capital to invest heavily in AI medical research. This largely solves the financial support required by AI medical research, and provides AI medical services. Further breakthroughs provide the driving force behind.
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