Artificial intelligence, AI, which finds patterns in complex biological data could eventually contribute to the development of individually tailored healthcare. Researchers at LiU have developed an AI-based method applicable to various medical and biological issues. Their models can for instance accurately estimate people’s chronological age and determine whether they have been smokers or not.
There are many factors that can affect which out of all our genes are used at any given point in time. Smoking, dietary habits and environmental pollution are some such factors. This regulation of gene activity can be likened to a power switch determining which genes are switched on or off, without altering the actual genes, and is called epigenetics.
Researchers at Linköping University (LiU) have used data with epigenetic information from more than 75,000 human samples to train a large number of AI neural network models. They hope that such AI-based models could eventually be used in precision medicine to develop treatments and preventive strategies tailored to the individual. Their models are of the autoencoder type, that self-organizes the information and finds interrelation patterns in the large amount of data.



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