Profiling Obese Subgroups in National Health and Nutritional Status Survey Data using Machine Learning Techniques – A Case Study from Brunei Darussalam

Usman Khalil, Owais Ahmed Malik, Daphne Teck Ching Lai and Ong Sok King
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Usman Khalil: School of Digital Science, Universiti Brunei Darussalam, Jalan Tungku Link, Brunei
Owais Ahmed Malik: School of Digital Science, Universiti Brunei Darussalam, Jalan Tungku Link, Brunei
Daphne Teck Ching Lai: School of Digital Science, Universiti Brunei Darussalam, Jalan Tungku Link, Brunei
Ong Sok King: Public Health Services, Ministry of Health, Brunei Darussalam and PAPRSB Institute of Health Sciences, Universiti Brunei Darussalam, Jalan Tungku Link, Brunei

Biomedical Journal of Scientific & Technical Research, 2023, vol. 48, issue 3, 39629-39643

Abstract: National Health and Nutritional Status Survey (NHANSS) is conducted annually by the Ministry of Health in Negara Brunei Darussalam to assess the population’s health and nutritional patterns and characteristics. The main aim of this study was to discover meaningful patterns (groups) from the obese sample of NHANSS data by applying the data reduction and interpretation techniques.

Keywords: Journals on Medical Drug and Therapeutics; Journals on Emergency Medicine; Physical Medicine and Rehabilitation; Journals on Infectious Diseases Addiction Science and Clinical Pathology; Open Access Clinical and Medical Journal; Journals on Biomedical Science; List of Open Access Medical Journal; Journals on Biomedical Engineering; Open Access Medical Journal; Biomedical Science Articles; Journal of Scientific and Technical Research (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:abf:journl:v:48:y:2023:i:3:p:39629-39643

DOI: 10.26717/BJSTR.2023.48.007641

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