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- Title
New Approach for Generating Synthetic Medical Data to Predict Type 2 Diabetes.
- Authors
Tagmatova, Zarnigor; Abdusalomov, Akmalbek; Nasimov, Rashid; Nasimova, Nigorakhon; Dogru, Ali Hikmet; Cho, Young-Im
- Abstract
The lack of medical databases is currently the main barrier to the development of artificial intelligence-based algorithms in medicine. This issue can be partially resolved by developing a reliable high-quality synthetic database. In this study, an easy and reliable method for developing a synthetic medical database based only on statistical data is proposed. This method changes the primary database developed based on statistical data using a special shuffle algorithm to achieve a satisfactory result and evaluates the resulting dataset using a neural network. Using the proposed method, a database was developed to predict the risk of developing type 2 diabetes 5 years in advance. This dataset consisted of data from 172,290 patients. The prediction accuracy reached 94.45% during neural network training of the dataset.
- Subjects
TYPE 2 diabetes; ARTIFICIAL intelligence; DATABASES; STATISTICS
- Publication
Bioengineering (Basel), 2023, Vol 10, Issue 9, p1031
- ISSN
2306-5354
- Publication type
Article
- DOI
10.3390/bioengineering10091031