AI-Assisted Prediction on Potential Health Risks with Regular Physical Examination Records
| Autor: | Guopeng Zhou, Yichun Duan, Zhaoqian Lan, Wei Yan |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Hospital information system
Service (business) 021103 operations research 020205 medical informatics medicine.diagnostic_test business.industry Computer science 0211 other engineering and technologies Physical examination 02 engineering and technology medicine.disease Electronic mail Health care 0202 electrical engineering electronic engineering information engineering medicine Medical emergency Healthcare service Health risk business Set (psychology) |
| Zdroj: | DSC |
| DOI: | 10.1109/dsc.2018.00056 |
| Popis: | With the development of society and economy, people pay more attention to their own health. The demand of more personalized health service is gradually rising. However, due to the lack of experienced doctors and physicians, most healthcare organizations cannot meet the medical demand of public. With the widespread use of hospital information system, there is huge amount of generated data which can be used to improve healthcare service. Thus, more and more data mining applications are developed to provide people more customized healthcare service. In this paper, we propose an AI-assisted prediction system, which leverages data mining methods to reveal the relationship between the regular physical examination records and the potential health risk. It can predict examinees' risk of physical status next year based on the physical examination records this year. The system provides a user-friendly interface for examinees and doctors. Examinees can know their potential health risks while doctors can get a set of examinees with potential risk. It is a good solution for the mismatch of insufficient medical resources and rising medical demands. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|