Risk Factors for Chronic Diabetes Patients

Oleg Metzker, Kirill Magoev, Stanislav Yanishevskiy, Alexey Yakovlev, Georgy Kopanitsa
2020 Studies in Health Technology and Informatics  
Specific predictive models for diabetes polyneuropathy based on screening methods, for example Nerve conduction studies (NCS), can reach up to AUC 65.8-84.7 % for the conditional diagnosis of DPN in primary care. Prediction methods that utilize data from personal health records deal with large non-specific datasets with different prediction methods. It was demonstrated that the machine learning methods allow to achieve up to 0.7982 precision, 0.8152 recall, 0.8064 f1-score, 0.8261 accuracy, and 0.8988 AUC using the neural network classifier.
doi:10.3233/shti200451 pmid:32570668 fatcat:rkwrw6u7ezfnjnub64ijndjsym