Research on Disease Prediction and Health Supplement Recommendation Algorithm Based on KNN Algorithm

In this paper, we propose an algorithm that can recommend personalized health functional foods considering diseases due to the high interest in health functional foods and the development of machine learning as society enters an aging phase. By applying the KNN algorithm, we presented a foundational framework for a platform for personalized health functional food recommendations through disease analysis, matching techniques of publicly available health functional food information, and national public data. To ensure reliable matching between diseases and health functional foods, we analyzed correlations, assessed the appropriateness and accuracy of variables for enhancing the KNN algorithm, and derived improvement directions for the proposed system through the improvement of learning models and information to be disclosed in the future.

Publication Details

Journal
Korean Institute of Smart Media
Published
2024-08-30
DOI
https://doi.org/10.30693/smj.2024.13.8.49
Primary Topic
Traditional Chinese Medicine Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

Research on Disease Prediction and Health Supplement Recommendation Algorithm Based on KNN Algorithm

Korean Institute of Smart Media
Traditional Chinese Medicine Studies
article

Research on Disease Prediction and Health Supplement Recommendation Algorithm Based on KNN Algorithm

article en

Abstract

In this paper, we propose an algorithm that can recommend personalized health functional foods considering diseases due to the high interest in health functional foods and the development of machine learning as society enters an aging phase. By applying the KNN algorithm, we presented a foundational framework for a platform for personalized health functional food recommendations through disease analysis, matching techniques of publicly available health functional food information, and national public data. To ensure reliable matching between diseases and health functional foods, we analyzed correlations, assessed the appropriateness and accuracy of variables for enhancing the KNN algorithm, and derived improvement directions for the proposed system through the improvement of learning models and information to be disclosed in the future.

Korean Institute of Smart MediaVol. 13(8)
Openalex Percentile: Top 71%
Traditional Chinese Medicine Studies
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