Another big data breakthrough is how Baidu transformed itself into a "Health Manager"

Source: Internet
Author: User

I have always been impressed by the Chinese supercomputer "Tianhe No. 1". Before that, I had only two words: "powerful". So when I saw that it was about to become a "unfinished building", like everyone else, except for sighing, only sighs. Even if you have powerful hardware and software computing capabilities, but cannot implement the practice, no matter how big the glory will be zero. This status is very similar to that of big data before January 1, 2012.

Therefore, the launch of Baidu disease prediction, China's first big data disease prediction system, can be regarded as a great event for China's medical industry and even China's public health management business. It declared that the public health management capability of big data had to say goodbye to the theory and entered the practical stage.

However, when big data really implements large-scale and multi-epidemic disease prediction, is its mission limited to prediction? No, there is more value in the future.

Disease prediction is applied to social value. The deeper layer is to explore data and mobilize the driving force behind disease prevention, achieve pre-management, and truly achieve the social welfare significance of big data: "from the people, ".

The Management Value of disease prediction enables business response management capabilities in the social service industry, such as the production and reserve of related medicines. Taking the flu that everyone is most familiar with as an example, the flu has a strong scalability and uncertainty. After using big data to predict the regions, times, and people that might erupt, pharmaceutical companies, drug stores, and other related enterprises can more targeted drug preparation, so as to reduce the extreme situation of blind storage or out of stock. In the outbreak of hepatitis disease, health management in the catering industry can be performed in advance to control the transmission of diseased people to healthy people.

That is to say, in the big data forecast environment, the management and business behavior of the entire medical industry will be achieved, and the user's needs will be best matched with the enterprise's supply, reducing the waste of resources.

The second aspect of management value is that, in addition to group public health management, it can be extended to individual health management. Disease prediction is more about predicting and intervening group behavior. However, with the popularization of mobile personal health equipment, this predictive management capability will not only achieve more accurate data collection, but also achieve point-to-point personal health prediction and management.

Currently, people familiar with mobile personal health devices can detect various health signs such as blood pressure, blood sugar, and heart rate. These are indicators related to hypertension, diabetes, and heart disease. Understanding the data and predicting the disease are of great value for personal health management. From the development trend, machine deep learning and medical enterprises will be more closely integrated in the future. This is mainly reflected in the fact that, through personal long-term health data collection, automatic identification and management of sudden changes can be realized, pre-prediction of patients and relevant medical solutions, such as drug solutions, hospital selection solutions, even family care solutions.

As an important reference tool for decision-making of Medical managers, disease prediction is applicable to more scenarios from decision-making to management, and more solutions can only be explored through close cooperation between big data and medical practitioners, so that big data prediction will not become the second "supercomputer ".

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