 |
International Society of Science and Applied Technologies |
| Predictions of Disease Onsets Using Medical Big Data | ||||
| Author | Naoki Tamada
|
|||
| Co-Author(s) | Masashi Kuwano; Yuka Minamino; Sota Hamaya
|
|||
| Abstract | This study contributes to the development of a health application designed to promote lifestyle improvements and disease prevention by providing personalized health information and visualizing an individual's health data. We developed a disease onset prediction system that calculates the probability of onset for seven diseases including serious diseases within the next three years using health checkup, medical care, and nursing care data from the National Health Insurance database. A deep neural network was utilized for these predictions. The study primarily investigates the temporal stability of the prediction model—an indicator of its versatility—by examining whether the model maintains its predictive accuracy when fed data from different years. Additionally, we assessed the impact of lifestyle modifications on disease onset probabilities by comparing predictions before and after hypothetical changes in individual lifestyle responses.
|
|||
| Keywords | Big Data on Health Screening, Medical Care and Nursing Care, Prediction of Disease Onset, Deep Neural Network, National Health Insurance Database | |||
| Article #: RQD2024-249 | ||||
Proceedings of 29th ISSAT International Conference on Reliability & Quality in Design |