Proceedings of the Korean Institute of Information and Commucation Sciences Conference (한국정보통신학회:학술대회논문집)
- 2022.10a
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- Pages.201-203
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- 2022
Predicting Blood Glucose Data and Ensuring Data Integrity Based on Artificial Intelligence
인공지능 기반 혈당 데이터 예측 및 데이터 무결성 보장 연구
Abstract
Over the past five years, the number of patients treated for diabetes has increased by 27.7% to 3.22 million, and since blood sugar is still checked through finger blood collection, continuous blood glucose measurement and blood sugar peak confirmation are difficult and painful. To solve this problem, based on blood sugar data measured for 14 days, three months of blood sugar prediction data are provided to diabetics using artificial intelligence technology.
최근 5년간 당뇨병으로 진료받은 환자가 322만 명으로 27.7% 증가하였으며 여전히 손가락 채혈을 통해 혈당을 확인하므로 연속적인 혈당 측정과 혈당 피크 확인이 어렵고 고통스러워한다. 이를 해결하기 위해 14일 간 측정한 혈당 데이터를 기반으로 인공지능 기술을 사용하여 3개월간의 혈당 예측 데이터를 당뇨 환자들에게 제공해준다.
Keywords
- SinGAN (Single Generative Adversarial Network);
- ADA (Adaptive Differentiable Augmentation);
- RNN (Recurrent Neural network);
- LSTM(Long Short Term Memory);
- GRU (Gated Recurrent Unit)