Kevin Co-Authors Published Medical Paper

August 18, 2020 at 11:47 AM

Since the end of November 2019, Year 12 student, Kevin He, has worked alongside a group of researchers from the Faculty of Health and Environmental Sciences at the Auckland University of Technology, and the Faculty of Health and Medical Sciences and the Faculty of Engineering and Bioengineering at The University of Auckland, and a fellow school student from Melbourne, who researched and prepared a medical paper for publication. Entitled, ‘Evaluation of Ethnic Variations in Visceral, Subcutaneous, Intra-Pancreatic, and Intra-Hepatic Fat Depositions by Magnetic Resonance Imaging (MRI) among New Zealanders,’ the paper has recently been released.

Kevin said that he has always had an interest in maths, science and the ‘computing side of things,’ so that long term, he hopes to become involved in an area of work that is STEM (Science, Technology, Engineering, Maths) related. When he heard about this project and the chance to become involved, it piqued his interest, as aside from the incredible opportunity to be involved in research of this calibre, the research may help so many people in the future.

Recent studies have shown that intra-hepatic and intra-pancreatic fat have emerged as important parameters for predicting certain cardio-vascular diseases and conditions such as diabetes and metabolic syndrome. Kevin said, ‘For this specific paper, I was involved in the collection and statistical analysis of data relating to the ethnic variation of visceral, subcutaneous, intra-hepatic and intra-pancreatic fat depositions in a cross section of the New Zealand community, including Europeans, Maori, Pacific Islanders and Asians.  In simpler terms, we looked at fat content in the body, especially in the pancreas using MRI to find and analyse relationships between different New Zealand ethnicities. We also took indices such as BMI, waist circumference and waist to height ratio to see if we could find any relationship with the fat depositions.

‘The data helped us to understand how we could better customise a machine-learning algorithm to be more accurate in identifying several types of fat content, especially intra-pancreatic fat which is associated with many diseases and conditions. This could have profound effects in the future, because if a machine can be developed to do identify this, medical experts will be greatly assisted in their diagnoses.’

Kevin said, ‘The learning curve was steep because I have had to learn a lot of new concepts and methods, as well as some frustrating processes, and still balance that with my IB Diploma work and extra-curricular activities at school, however, if someone has the determination and the time organisation to do it, it is totally possible.’

Kevin is grateful to Professor Jun Lu, Head of Research at Auckland University of Technology for giving him this incredible opportunity.

Click here to view the published paper 


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