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Artificial Neural Network analysis of hydrocarbon profiles for the ageing of Lucilia sericata for Post Mortem Interval estimation

<29>Currently, expert forensic entomologists/analytical chemists must inspect volatile hydrocarbon gas-chromatography (GCMS) data in subjective and labour intensive ways, to determine a post-mortem interval based on entomological scene of crime samples. This paper is the first to show that a self-organising map neural network can systematically and accurately automate the clustering and classification of the GCMS profiles of insect larvae varying in age from one to nine days old. Since its presentation at the leading European forensic entomology conference (April 2013) this work has led to collaboration requests from the UK Natural History Museum and researchers in Germany and the US.