Big data, along with the advancement of AI, machine learning and data science, help forecast nCoV epidemic, said Tran Quoc Tuan, Master of Computer Science and FUNiX mentor of Data Science and Machine Learning.
The spread of China’s deadly coronavirus are triggering a global health emergency. Unlike other previous pandemics, information and accurate predictions about the epidemic trend are being provided clearly and timely. Besides global efforts in health, outbreak control and prevention are also supported by technology, including data science, machine learning and artificial intelligence.
Various websites update latest information about the nCoV epidemic
As the outbreak has sparked fear and anxiety around the world, latest news about the coronavirus have been accessible in many websites. Some of them are https://corona.kompa.ai designed by Vietnamese engineer team, or www.coronatracker.com. Data and information, including the number of cases, death toll, cured cases, geographical distribution, are constantly updated and reported.
The advancements of data statistics over the past ten years have given viewers a concrete and intuitive view of the data. Instead of using charts solely, the R language has created a visualization of the data with vivid colors, charts, and images.
Corona Tracker utilizes such data science methods as NLP (natural language processing) to analyze content and identify meaningful topics and AWS for news storage. The API and part of CoronaTracker.com were built with Vue.js and backend with Node.Js and ExpressJS.
Kompa Group’s Corona website provides information about hotspots and specific numbers of the outbreak. The data on the site is updated continuously from such sources as WHO, CDC, NHC, DXY and Ministry of Health. The team also detect and filter out misinformation by using machine learning.
In fact, data and AI can even help prevent the disease. In late December, BlueDot, a Canadian company that monitors infectious diseases worldwide, spotted the coronavirus with support of AI, before the warning of the Centers for Disease Control and Prevention on January 6th.
BlueDot analyzed a large amount of data about plant and animal pathologies and conducted official sources reported by government agencies and other sources. This research helped prevent its customers from travelling to China over the past few months. In addition, it is also forecasted that the epidemic will soon appear in Seoul, Tokyo, Bangkok, etc.
BlueDot processed data by using natural language processing (NLP) and machine learning (ML) in real time, such as Arima, Time Series, Bayes, etc. A large amount of unstructured text data (millions of copies) from over 60 languages were being processed to track more than 100 different diseases. AI had also been applied to minimize the role of dozens to hundreds of people.
Results by the AI system (including machine learning and deep learning) were analyzed by doctors and epidemiologists and updated each hour so that recommendations were given to relevant official departments and citizens. These results helped experts focus on combating coronavirus, rather than other time-wasting works.
Previously, BlueDot had successfully predicted the location of Zika epidemic in South Florida, according to The Lancet (UK).
How science helps prevent the outbreak?
BlueDot is not the only company that has successfully adopted AI in Corona epidemic. As AI has been widely utilized in health care, it can predict the number of new infections according to age, gender and geographical factors and according to different rates and risks. Furthermore, it also forecasts global disease hotspots and the spread of the outbreak based on environmental conditions, care, resilience and transmission methods.
Besides, AI can enhance optimization in disease prevention strategies. For example, machine learning can help assess accuracy and optimize quarantine among communities, cities and countries to control the spread of the disease. AI can also identify similarities in local outbreaks, for instance, the link between Corona and SARS.
Moreover, machine learning, an essential part of AI, helps researchers read billions pieces of data and clinical results from medical records and establish connections with patients. Machine learning assists doctors in predicting transmission methods of patients and build a model or relationship between treatments documented in a patient’s medical record and condition. In genetics, the Boltzman helps stimulate the body’s immune system by using AI algorithms.
In the changing world, epidemics are emerging and spreading much more quickly. With the increase in the role of science and technology, information and prevention will be faster and more timely.
Source: VnexpressRelated posts: