Source: Beijing News Author: Wang Xiao (Beijing News Urban Institute researcher wisdom) Editor: Libi Ying proofread: Wu hair
At the end of 2019, a new coronavirus pneumonia epidemic situation appeared in Wuhan. The epidemic quickly spread to provinces and cities across the country. As of 14:00 on February 1, 2020, the number of people diagnosed with pneumonia in mainland China has reached 11,844, far more than the number of people diagnosed in mainland China during the SARS period in 2003.
In the past few years, we have been very familiar with new technologies such as artificial intelligence, big data, and blockchain. So what role do these technologies have in responding to the current epidemic prevention and control? Compared to 2003, what kind of progress can these technological advances bring to us?
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In response, the Beijing News reporter connected a number of experts and scholars to discuss how AI can enable anti-epidemic and development in public health emergencies.
Interviewed guests (ranked by last name Pinyin):
Yi Jingtao (Professor, School of Business, Renmin University of China)
Nandi Zhang (Dean of Renmin University of China, Qingdao Branch, Associate Professor, School of Public Management)
Zuo Meiyun (Researcher, Social System Engineering Research Center, National Development Institute, Renmin University of China, Vice Dean, School of Information, Renmin University of China)
Leverage the advantages of AI technology, predict the scale of demand, and make up for shortcomings in human and resources
Beijing News: In what ways do you think AI technology can empower public health emergencies?
Zhang Nandiyang: I think that AI can effectively supplement the lack of social organizations and social workers in grass-roots communities, especially in rural areas, in terms of intelligent care. During the whole society's efforts to respond to the epidemic, a large amount of human and material resources were invested in the mechanism of confirmed cases and the follow-up investigation of suspected cases, which relatively ignored the assistance to vulnerable groups. A tragic incident occurred in Huanggang, Hubei Province, where the family was isolated from cerebral palsy due to lack of care.
To a certain extent, it is difficult for us to predict the scale of public health emergencies and the scale of resource demand in concentrated outbreak sites. After the outbreak of the crisis, smart nursing equipment can make up for areas with limited resources and insufficient nursing power, especially nursing needs, but nursing awareness, conditions and capabilities cannot meet the needs of rural areas.
In addition, the significance of AI care in public health crisis events is even more important. After the patient is rescued, a large amount of time needs to pass the dangerous period in effective care or complete rehabilitation. Nowadays, a large number of front-line care workers risk their lives and work hard. The use of intelligent care can effectively protect the safety of medical staff and reduce the risk of infection. .
Of course, AI monitoring population movements also has important technical support for similar public health crisis events. Based on mobile phone data, promote the use of blockchain technology to track population flow and pool, and share large-scale, large-scale, multi-point data in real-time with relevant departments and institutions for real-time sharing. The distributed, traceable, and tamper-resistant features of the blockchain can greatly improve the efficiency of data sharing and accurate tracking, thereby helping to accurately identify the trajectory of people and provide strong support for the classification and accurate tracking and monitoring of crisis populations.
Zuo Meiyun: Face recognition technology and mobile communication positioning technology can play a great role in monitoring population movement. In terms of face recognition technology, once a patient is diagnosed with a new coronary pneumonia case, he or she can quickly upload an image of his or her face, and query his or her movement trajectory in the Skynet system of the Ministry of Public Security to find out the possible Close contacts. For mobile communication positioning technology, through mobile phone positioning, a list of returning people passing through Wuhan and even Hubei is made. One is to give them tips to pay attention to self-protection, and the other is to inform the destination city of the return in advance so that it can make it early. ready.
In terms of smart care, for delivering food and clothing to isolated people, streets or communities with conditions can put smart service robots to use. In the future, in terms of treatment. It is also possible to consider the use of robotic treatment for mild patients. As long as the patient can move freely, he can communicate with the doctor and perform operations through a medical robot. For example, the first infected person with a new type of coronavirus found in Seattle, USA is now in an isolation room and is completely treated by intelligent robots. In this way, the chance of transmission of the new crown pneumonia virus can be reduced, and the workload of the doctor will be greatly reduced.
Combining deep learning algorithms with patient dynamic data to provide a reference for the development of new drugs
Beijing News: What role do you think AI can play in the fight against epidemics? Hope to explain it better in combination with domestic and foreign cases.
Zuo Meiyun: At present, for patients with mild new crowns, symptomatic treatment is mainly given, and corresponding life support is given. For severe patients, many hospitals and doctors are actively trying to use some drugs previously used in other similar respiratory diseases for exploratory treatment. This is very important. For critically ill patients, we must pay attention to accumulating dynamic effect data of patients after use. In this way, it is possible to find effective existing drugs for treatment, or to combine these data with AI technology to develop new drugs in future product development.
Based on big data abroad, association analysis of drugs and symptoms has been obtained, and some drugs have positive side effects. We can also use similar methods to find available drugs. In the development of new drugs in the future, the molecules and elements of these drugs are considered as inputs, and deep learning algorithms are designed to test which combinations can effectively alleviate the symptoms of new crown patients, so as to provide a reference for the development of new drugs.
Yi Jingtao: The three core elements of artificial intelligence AI include data, computing power, and algorithms. These three elements are indispensable and have become the necessary conditions for the success of artificial intelligence. The new Wuhan coronavirus that swept the country this time, because the virus has new characteristics such as long incubation period, strong infectivity, and asymptomatic infection, has indeed brought huge challenges to the traditional thinking and logic of governance and prevention.
In the fight against epidemics, artificial intelligence has obvious early warning function
Artificial intelligence has broken through the bottlenecks of traditional governance in the areas of early warning, prevention and treatment of epidemics. It has provided new ideas, methods and means for epidemic prevention and control, and has provided a lively source for epidemic prevention and control in the new era of the digital economy. Experience and new attempts.
In terms of anti-epidemic, AI early warning function is obvious. Canadian AI company Bluedot uses AI-driven algorithms to search its foreign language news reports and animal and plant disease reports to warn its customers on December 31, 2019 to reduce activities in Wuhan and other regions. The news released on January 6, 2020 is still early.
In research and development, AI-assisted vaccines and new drug development also have precedents. In July 2019, an Australian research team used AI to help develop an influenza vaccine that can stimulate the human immune system to produce more anti-influenza virus antibodies than ordinary vaccines.
During the epidemic in China, Alibaba Cloud also opened all AI computing power to global public scientific research institutions for free to accelerate the development of new pneumonia drugs and vaccines. Baidu Research Institute is free to open the linear time algorithm LinearFold to all genetic testing institutions, epidemic prevention centers and scientific research centers around the world to improve the prediction speed of the new coronavirus RNA spatial structure.
In addition, there are new breakthroughs in the application of AI in treatment. According to the British "Guardian" reported on January 22, a medical institution in Washington, U.S.A., used robots to treat the first patient with a new type of coronavirus pneumonia in the United States. A robot equipped with a microphone, camera, and stethoscope is installed in the patient's ward to observe and treat the patient. The patient's treatment has been satisfactory so far.