Artificial intelligence to fight infectious diseases
Abstract
Throughout human history, the epidemic crisis has always existed.Establishing a perfect system to fight against it is an important survival battle for human beings.The key to reducing the pandemic is the early detection of potential pathogens before a massive outbreak, giving public health departments and researchers ample time to respond, but this is not easy.Microsoft uses A I technology and genomics to monitor scalable monitoring to detect infectious disease threats early, such as continuous monitoring how specific insect types (such as mosquitoes) transmit pathogens through the blood, Microsoft’s cloud genome also tries to identify and analyze all biological and virus types in the environment to determine early patterns of disease transmission.Microsoft also use A I in infectious disease diagnosis —— on the basis of a lot of infection data training, AI can through the analysis of data and image scanning, assist the grassroots inspection department to identify infection pathogen intelligent algorithm, intelligent image recognition to help grassroots doctors identify different kinds of fungi, improve the detection rate of infection pathogens, so as to provide accurate and personalized medical services.Dai Beijie, senior project manager at Microsoft Asia Research Institute, will also introduce how Microsoft can use A I technology to improve human awareness of infectious diseases, strengthen the fight against the epidemic, and drive the development of human health care through scientific and technological innovation.
Analysis
This case well reflects the principle of A I benefit to the people advocated by SenseTime. The original intention of A I application should be inclusive, taking meeting people’s yearning for a better life as the landing point of scientific and technological innovation.Health is the premise and foundation for people to achieve a better life. During the epidemic, super transmissionists played a key role in the transmission of the virus. The traditional use of manual investigation is low efficiency, second, many potential virus transmission relations are easy to be missed, losing the opportunity to find or control super communicators.Rapid classification of disease files through machine learning, the establishment of virustransmission path and transmission relationship, are conducive to the early investigation of super communicators, and effectively control the development of the epidemic to malignant transmission. This case is also in line with the pursuit of the Sustainable Development Goals (SDG3), eliminating the elimination of harm to human health caused by infectious diseases and promoting the health and well-being of all age groups.
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