Deep Learning-Based Health Management Model Application in Extreme Myopia Eye Vision Monitoring and Risk Prediction. (12th October 2022)
- Record Type:
- Journal Article
- Title:
- Deep Learning-Based Health Management Model Application in Extreme Myopia Eye Vision Monitoring and Risk Prediction. (12th October 2022)
- Main Title:
- Deep Learning-Based Health Management Model Application in Extreme Myopia Eye Vision Monitoring and Risk Prediction
- Authors:
- Huang, Zhaoxia
Xu, Xue
Cheng, Wenhui - Other Names:
- Cigerci İbrahim Hakkı Academic Editor.
- Abstract:
- Abstract : According to statistics released by the WHO, China has the highest prevalence of myopia in the world, with a frequency that is 1.5 times higher than the global average. Asians have the highest prevalence of myopia worldwide. The Ministry of Education and the State General Administration of Sports "2010 National Student Physical Fitness and Health Research Results" show that the incidence of poor vision among primary and secondary school students in China is 67.3%, and elementary school students' vision has decreased by 40.9%. Low vision among youth has become a major cause of affecting the quality of the population and improving national physical fitness; therefore, how to improve and enhance the vision level of youth has become a major issue for the government, sports, and educators face as a major issue. In order to address this issue, this research suggests a deep learning-based vision monitoring and risk prediction model for high myopia eyes and develops a deep artificial neural network that unsupervised learns essential characteristics of physiological time-series data.
- Is Part Of:
- Journal of oncology. Volume 2022(2022)
- Journal:
- Journal of oncology
- Issue:
- Volume 2022(2022)
- Issue Display:
- Volume 2022, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 2022
- Issue:
- 2022
- Issue Sort Value:
- 2022-2022-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-10-12
- Subjects:
- Oncology -- Research -- Periodicals
Tumors -- Periodicals
Neoplasms
Oncology -- Research
Tumors
Periodicals
Periodicals
616.994 - Journal URLs:
- https://www.hindawi.com/journals/jo/ ↗
http://www.pubmedcentral.nih.gov/tocrender.fcgi?journal=859&action=archive ↗ - DOI:
- 10.1155/2022/4537021 ↗
- Languages:
- English
- ISSNs:
- 1687-8450
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 24166.xml