Release date: 2017-07-21

Last week, the official landing of Ali's unmanned supermarkets set off a wave of public opinion, and it was also questionable when it became attractive. From March 2016, Li Shishi battle Alphago, artificial intelligence (AI) began to quickly enter the public eye, and when Foxconn robots went to the assembly line, Jingdong began to use robotic delivery, Li Yanhong took the driverless car to the Beijing Fifth Ring, like the Internet Similarly, it will become the key word for changing human life, it will become the revolutionary technology of the next era, and behind it is the billion-scale artificial intelligence industry market.

In the medical health and pharmaceutical industries, AI technology can be said to be a direct pain in the industry. With the aging of the population, the increasing demand for value-based medical services, and the shortage of global healthcare professionals, AI+ healthcare is becoming the next hotspot. The giants have accelerated the layout of the artificial intelligence industry, and large pharmaceutical companies have also tried water.

Internet giants seize data high ground

On March 29th, Ali released the ET medical brain and announced its formal entry into the medical AI field. Based on massive data and deep learning algorithms, ET Medical Brain can be used as a doctor assistant in various fields such as disease risk prediction, imaging diagnosis, precision treatment, and health management. To reduce the workload of medical staff.

In just over three months, Ali Health has made breakthroughs in the field of diagnostic imaging.

On July 11, Ali Health launched the medical diagnostic AI product “Doctor You”, which includes clinical medical research diagnostic platform, medical auxiliary monitoring engine, and physician ability training system. At the launch site of the Wanliyun Medical Imaging Center in Beijing, “Doctor You” demonstrated the real application scenario of the CT lung nodule intelligent detection engine in the remote imaging diagnosis process, which was nearly 9000 for 30 patients in the 30-minute diagnosis time. The CT image is intelligently detected, and the accuracy of identifying lung nodules is over 90%, while the traditional consultation method takes 5-6 times.

Ali is advancing on the road to lung cancer diagnosis. Another Internet giant, Google, has another face in breast cancer diagnosis. In a competition with human medical experts to analyze breast cancer cases, scientists from Google Brain and Verily developed an artificial intelligence diagnosis accuracy of 88.5% for breast cancer diagnosis, which is better than the 73.3% accuracy of the famous human pathologist. .

When it comes to AI+ healthcare, IBM Waston has to be mentioned. In the medical field, most companies' AI products are still in the research and development stage. Only IBM Watson has settled in China.

IBM has been developing Watson since 2006. By studying the literature, Watson is able to screen millions of patient records in decades of cancer treatment history, including medical records and patient treatment results, and provide physicians with options to choose from within a few seconds. Evidence-based treatment options.

Focusing on tumors, Watson has made breakthroughs in nine major medical fields, including chronic disease management, precision medicine, and in vitro testing, and began to serve doctors and patients. In August 2016, he officially entered China to test water. Currently, the top three hospitals in the field of cancer treatment are running Watson. On March 28, 2017, Watson signed a contract with Baiyang Intelligent Technology Co., Ltd., which is a subsidiary of Baiyang Pharmaceutical Group, and officially entered the Chinese market.

The breakthrough of artificial intelligence diagnosis and the improvement of accuracy in the future will perfectly fit the rapid development of the third-party imaging industry, making the image cloud diagnostic platform the ultimate solution for image diagnosis.

Foreign drug companies test water new drug research and development

The new drug development cycle is long, the cost is high, and the success rate is low. Artificial intelligence can make up for the limitations of new drug mining. Unlike the Internet giants who seized data from the upstream and the layout diagnostics, the eyes of the pharmaceutical giant focused on the new drug development business. Just last week, GlaxoSmithKline, the world's top 10 pharmaceutical company, announced a $43 million deal with Exscientia, an artificial intelligence startup. GlaxoSmithKline will develop dozens of drugs through the Exscientia artificial intelligence platform. “Many large pharmaceutical companies are beginning to realize the potential of this approach and how it can help increase efficiency,” said Exscientia CEO Andrew Hopkins, Exscientia. New drug screening can be done in just a quarter of the time and cost of traditional methods. In addition to GlaxoSmithKline, Sanofi also signed a cooperation agreement with Exscientia in May.

In December last year, Pfizer and IBM announced a partnership, Pfizer will use IBM Waston to assist in drug discovery for cancer immunotherapy. “I’m working in an industry that takes 12 years to launch a product,” said Judy Seward, Pfizer’s vice president of digital strategy and data innovation, at the “Guangming Forum”. “In the meantime, there were 1600 Scientists are involved in the research, and 3,600 clinical trials involve thousands of patients. We began to think about how to make artificial intelligence speed up the process, making it more intelligent to connect breakthrough medicine and connect patients who need it the most.

In order to make the drug development process smoother, pharmaceutical giants such as Merck, Johnson & Johnson, and Novartis are also increasing their cooperation with artificial intelligence companies to jointly develop the potential of artificial intelligence new drugs. At present, a number of artificial intelligence-led drug development companies have emerged, such as TwoOXAR, Atomwise, Insilico Medicine, Berg Health, etc.

Domestic enterprise layout auxiliary treatment

China Internet and IT industry mainstream business magazine "Internet Weekly" announced the "2017 Internet Weekly" future task TOP100", including the medical artificial intelligence team Airdoc founder Zhang Dalei high fourth. The prospects of AI+ healthcare can be seen. In 2017, AI+ medical fever is increasing. What is the development trend and trend of domestic AI+ healthcare? This year, CBInsights tracked a hundred health care companies focused on artificial intelligence. Since January 2015, 50 companies have made initial public offerings. The number of AI startups focused on medical sales increased from less than 20 in 2012 to nearly 70 in 2016.

In recent years, domestic policies have been intensively introduced, and the strategic position of artificial intelligence has continued to rise. The “Government Work Report” issued by the State Council in 2017 proposes to accelerate the cultivation and expansion of emerging industries and fully implement strategic emerging industry development plans, including artificial intelligence and biopharmaceuticals. After the “healthy China” rises to the national strategy, the application prospects of big data and artificial intelligence in the medical field are more broad and clear.

Big data and artificial intelligence in the health field are industries that require long-term high investment. The proportion of startups that use artificial intelligence for drug excavation is higher, while domestic companies prefer to have quicker and easier access. In the domestic healthcare subdivision, the amount of supplementary medical treatment is the highest, followed by It is voice interaction, medical imaging, and health management.

According to the statistics of the HSMAP system created by Flint, there are currently 139 domestic medical artificial intelligence related companies, mainly distributed in Beijing, Guangzhou and the Yangtze River Delta.

For a long period of time, China's AI will still be in a relatively early stage, and there is huge room for future development, especially in the field of big data, but for the medical and health industry, the application of artificial intelligence will be relatively slow and cautious. This is not only because the innovation cost of the pharmaceutical industry is higher, but more importantly, in this field, an algorithm error may lead to the difference between life and death.

Source: Xinkangjie (Micro Signal XKJ0101)

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