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Abstract In medical domain, risk factors are often used to model disease predictions. In order to make the most use of the predictive models, linking the model with real patient… Click to show full abstract
Abstract In medical domain, risk factors are often used to model disease predictions. In order to make the most use of the predictive models, linking the model with real patient data generates personalized disease progression and predictions. However, the risk factors are fragmented all over medical literature, certain risks can be accumulated for a disease and the aggregated probability may increase or decrease the occurrence of a disease. In this paper, a risk predictive framework which forms a base for a complete risk prediction model that can be used for various health applications is proposed.
Journal Title: Healthcare Technology Letters
Year Published: 2022
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