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Nathaphon Boonnam. Optimizing machine learning approaches for personalized food recommendation systems in non-communicable disease management. (). King Mongkut's University of Technology North Bangkok. Central Library. : , 2025.
Optimizing machine learning approaches for personalized food recommendation systems in non-communicable disease management
Name: Surat Lawdi
Organization :
Prince of Songkla University. Faculty of Science and Industrial Technology
Email :
suratlhaodee@gmail.com
Name: Nathaphon Boonnam
Organization :
Prince of Songkla University. Faculty of Science and Industrial Technology
Email :
nathaphon.b@psu.ac.th
LCSH:
Machine learning
LCSH:
Precision medicine
LCSH:
Diet therapy
LCSH:
Chronic diseases
Abstract:
This paper presents a comprehensive analysis of machine learning methodologies for developing personalized food recommendation systems tailored to the management of non-communicable diseases (NCDs). The study evaluates the effectiveness of various algorithms, including content-based filtering, collaborative filtering, deep generative models, and hybrid approaches, in delivering nutritionally appropriate and individualized dietary guidance. Among the algorithms tested, the Random Forest algorithm achieved the highest accuracy at 91.8%, followed by the K-Nearest Neighbors (KNN) algorithm at 89.5%, and the Multi-Layer Perceptron (MLP) algorithm at 85.0%. The findings highlight the significant potential of personalized food recommendation systems to support individualized nutrition.
King Mongkut's University of Technology North Bangkok. Central Library
Address:
BANGKOK
Email:
library@kmutnb.ac.th
Created:
2025
Modified:
2026-01-08
Issued:
2026-01-08
บทความ/Article
application/pdf
BibliograpyCitation :
In IEEE Thailand Section. Antennas and Propagation/Electron Devices/Microwave Theory and Techniques Joint Chapter, Electrical Engineering/Electronics, Computer, Telecommunications, and Information Technology Association, and King Mongkut's University of Technology North Bangkok. The 5th Research, Invention and Innovation Congress (RI2C 2025) (pp.251-253). Bangkok : IEEE Thailand Section
eng
©copyrights King Mongkut's University of Technology North Bangkok
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0.037153 วินาที
Surat Lawdi
| Title | Contributor | Type |
|---|---|---|
| Optimizing machine learning approaches for personalized food recommendation systems in non-communicable disease management
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Surat Lawdi;Nathaphon Boonnam | บทความ/Article |
Nathaphon Boonnam
| Title | Contributor | Type |
|---|---|---|
| Efficiency measurement of energy yield from solar photovoltaic cell with embedded system of alternative clamp meter
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Orachon Lanteng;Nathaphon Boonnam | บทความ/Article | |
| Osteoporosis prognosis through machine learning analysis of x-ray films
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Jiranuwat Massatith;Nathaphon Boonnam;Rattanasak Hama | บทความ/Article | |
| Optimizing machine learning approaches for personalized food recommendation systems in non-communicable disease management
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Surat Lawdi;Nathaphon Boonnam | บทความ/Article | |
| Comparative analysis of deep learning models for nutrition table detection in food product images
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Mintira Sae-Eia;Nathaphon Boonnam | บทความ/Article |