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Development of Score Based Smart Risk Prediction Tool for Detection of Type-1 Diabetes: A Bioinformatics and Machine Learning Approach
Biointerface Research in Applied Chemistry
In this study, a smart risk prediction tool has been demonstrated along with the algorithm, which works as a backend of the tool to detect Type-1 Diabetes. The algorithm was contrived by the weightage values that are articulated by analyzing the risk factors of Type-1 diabetes. The analysis takes place with a machine learning and statistical approach. Data were collected from a number of cases and control groups, which was preprocessed to be fit for the analysis. Risk factors were extracted bydoi:10.33263/briac112.90079016 fatcat:6wntaqdbljdmxjxf32nxphshjy