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R.L. Kennedy

Researcher at Deakin University

Publications -  35
Citations -  1333

R.L. Kennedy is an academic researcher from Deakin University. The author has contributed to research in topics: Obesity & Type 2 diabetes. The author has an hindex of 16, co-authored 35 publications receiving 1172 citations. Previous affiliations of R.L. Kennedy include Barwon Health & Queen's University.

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Journal ArticleDOI

Measurement of retinal vessel widths from fundus images based on 2-D modeling

J.A. Lowell, +5 more
TL;DR: An algorithm to measure the vessel diameter to subpixel accuracy is presented, based on a two-dimensional difference of Gaussian model, which is optimized to fit aTwo-dimensional intensity vessel segment.
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Risk stratification using data from electronic medical records better predicts suicide risks than clinician assessments

Truyen Tran, +9 more
- 14 Mar 2014 - 
TL;DR: Predictive models applied to data from the EMR could improve risk stratification of patients presenting with potential suicidal behaviour, and include known risks for suicide, but also other information relating to general health and health service utilisation.
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Obesity in the elderly: who should we be treating, and why, and how?

R.L. Kennedy, +2 more
- 01 Jan 2004 - 
TL;DR: Obesity is a common problem in the elderly, although its prevalence decreases in extreme old age, and prevention and treatment programmes have the potential to decrease the impact of diabetes, vascular disease, and other complications of obesity.
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Hydroxyoctadecadienoic acids: Oxidised derivatives of linoleic acid and their role in inflammation associated with metabolic syndrome and cancer.

Venkat N. Vangaveti, +3 more
- 15 Aug 2016 - 
TL;DR: The role of LA derivatives and their actions on regulation of inflammation relevant to metabolic processes associated with atherogenesis and cancer are examined, which may help drive processes that could regulate inflammation in a beneficial manner.
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Machine-learning prediction of cancer survival: a retrospective study using electronic administrative records and a cancer registry

Sunil Gupta, +15 more
- 01 Mar 2014 - 
TL;DR: Machine learning applied to information from a disease-specific (cancer) database and the EAR can be used to predict clinical outcomes, and the model performed consistently across a range of cancers, including rare cancers.