Machine learning-based nutrient classification recommendation algorithm and nutrient suitability assessment questionnaire

• JaHyung Koo,
• LanMi Hwang,
• HooHyun Kim,
• TaeHee Kim,
• JinHyang Kim,
• HeeSeok Song,

Vol. 17, No. 1, January 31, 2023
10.3837/tiis.2023.01.002, Download Paper (Free):

• Machine Learning
• Classification
• Nutrient Deficiency
• smart healthcare
• adaptive algorithm
• Questionnaire

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.

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