Published on in Vol 8 (2023)
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/49113, first published
.
![A Machine Learning Web App to Predict Diabetic Blood Glucose Based on a Basic Noninvasive Health Checkup, Sociodemographic Characteristics, and Dietary Information: Case Study A Machine Learning Web App to Predict Diabetic Blood Glucose Based on a Basic Noninvasive Health Checkup, Sociodemographic Characteristics, and Dietary Information: Case Study](https://asset.jmir.pub/assets/2c4d15d7253800fa329a554259006db6.png 480w,https://asset.jmir.pub/assets/2c4d15d7253800fa329a554259006db6.png 960w,https://asset.jmir.pub/assets/2c4d15d7253800fa329a554259006db6.png 1920w,https://asset.jmir.pub/assets/2c4d15d7253800fa329a554259006db6.png 2500w)
Journals
- Pande H, Kapse S, Krishnan V, Kausley S, Satyavathi C, Rai B. Prediction of Shelf Life of Pearl Millet Flour Based on Rancidity and Nutritional Indicators Using a Long Short-Term Memory Network Model. ACS Food Science & Technology 2024;4(3):786 View