TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
Machine learning-based nutrient classification recommendation algorithm and nutrient suitability assessment questionnaire |
| 영문제목(English Title) |
Machine learning-based nutrient classification recommendation algorithm and nutrient suitability assessment questionnaire |
| 저자(Author) |
JaHyung Koo
LanMi Hwang
HooHyun Kim
TaeHee Kim
JinHyang Kim
HeeSeok Song
|
| 원문수록처(Citation) |
VOL 17 NO. 01 PP. 0016 ~ 0030 (2023. 01) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
The elderly population is increasing owing to a low fertility rate and an aging population. In addition, life expectancy is increasing, and the advancement of medicine has increased the importance of health to most people. Therefore, government and companies are developing and supporting smart healthcare, which is a health-related product or industry, and providing related services. Moreover, with the development of the Internet, many people are managing their health through online searches. The most convenient way to achieve such management is by consuming nutritional supplements or seasonal foods to prevent a nutrient deficiency. However, before implementing such methods, knowing the nutrient status of the individual is difficult, and even if a test method is developed, the cost of the test will be a burden. To solve this problem, we developed a questionnaire related to nutrient classification twice, based upon which an adaptive algorithm was designed. This algorithm was designed as a machine learning based algorithm for nutrient classification and its accuracy was much better than the other machine learning algorithm. |
| 키워드(Keyword) |
Machine Learning
Classification
Nutrient Deficiency
smart healthcare
adaptive algorithm
Questionnaire
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| 파일첨부 |
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