Published: Cluster Analysis for Identifying Obesity Subgroups in Health and Nutritional Status Survey Data

MSc in Computer Science student, Usman Khalil has published research in Asia-Pacific Journal of Information Technology and Multimedia (APJITM). Well done!

Usman Khalil, MSc in Computer Science, co-supervised by Dr Owais Malik and Dr Daphne Lai has published his paper, Cluster Analysis for Identifying Obesity Subgroups in Health and Nutritional Status Survey Data, at the Asia-Pacific Journal of Information Technology and Multimedia (APJITM). This research was a collaboration with Dr Ong Sokking, Ministry of Health, Brunei. His masters project was in the investigation of machine learning techniques to identify meaningful patterns in the health and nutritional survey data.

Excerpt of abstract:

“This study presents the discovery of meaningful patterns (groups) from the obese samples of health and nutritional survey data by applying various clustering techniques. Due to the mixed nature of the data (qualitative and quantitative variables) in the data set, the best-suited clustering techniques with appropriate dissimilarity metrics were chosen to interpret the meaningful results. The relationships between obesity and the lifestyle affecting factors like demography, socio-economic status, physical activity, and dietary behavior were assessed using four cluster techniques namely Two-Step clustering, Partition Around Medoids (PAM), Agglomerative Hierarchical clustering and, Kohonen Self Organizing Maps (SOMs).”

The following are papers published by Usman during his Masters:

1. Profiling Obese Subgroups in National Health and Nutritional Status Survey Data Using Categorical Principal Component Analysis -A Case Study from Brunei Darussalam, U Khalil, OA Malik, DTC Lai, SK Ong, Asia-Pacific Journal of Information Technology and Multimedia (APJITM), Vol 10, No 2, December 2021

2. Profiling Obese Subgroups in National Health and Nutritional Status Survey Data Using Categorical Principal Component Analysis -A Case Study from Brunei Darussalam, U Khalil, OA Malik, DTC Lai, SK Ong, International Conference on Integrated Technology (ICIT 2019)

3. Identifying sub-groups of the obese from national health and nutritional status survey data using machine learning techniques, U Khalil, OA Malik, DTC Lai, OS King, IET Digital Library, 7th Brunei International Conference on Engineering and Technology 2018 (BICET 2018)

Usman Khalil is currently a PhD in Computer Science student at the School of Digital Science, Universiti Brunei Darussalam, working in computer vision under the supervision of Dr Owais Malik and Dr Ong Wee Hong.

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