Health risk can be determined with an AI-based smartphone application

Technology

The healthcare cost has been rising at a startling pace and at the same time, even many health conditions are not addressed at the appropriate time. With an aim to overcome this issue, VTT Technical Research Centre of Finland has come up with an artificial intelligence-dependent data analysis techniques used in a smartphone app of Odum Ltd. The app enables the user to determine their health risk, and if needed, also direct them toward a better lifestyle.

The app has 2 diverse segments, namely, the health exam and the prediction. First, the prediction asks over ten questions and then a machine learning algorithm estimates the possibility of becoming unwell. On the basis of the outcomes, the app directs the user to go on with a health exam accomplished within the application. The user is asked about 10 diverse health factors (approximately 52 questions) and then gets personal outcomes and feedback for every health factor.

The feedback is generated by a multifaceted group of medical professionals; it might be positive and ask the users to keep up with their good work, direct them to make a transformation in their lifestyle, or to visit a medical professional. In case the user is already taking medications, they feedback might tell them to pursue the treatment schedule they have. Once the prediction is accomplished, the app will generate reminders on the basis of outcomes to prompt the user when he/she should carry out the next prediction. If the outcome is “high risk,” the user should take a new prediction in 30 days. Similarly, for “medium risk” and “low risk,” the user should take a new prediction in 60 and 90 days, respectively.

During the project, VTT and Odum studied health data gathered from 18 to 64-year olds over the duration of many years. The project obtained health records from a sum of 120,000 working individuals. It consists of self-assessments about alertness/sleep, the ability to work, exercise habits, alcohol consumption, type of work the respondent does, weight, use of tobacco products, mood, pain, and diabetes risk.

Don’t you think it is a good way of decreasing the healthcare costs and also improve the quality of life of an individual?

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