Machine Learning Based Multimodal Neuroimaging Genomics Dementia Score for Predicting Future Conversion to Alzheimer’s Disease - IOS Press

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Combining genetics and brain MRI can aid in predicting chances of Alzheimer's disease sfu IOSPress_STM

Mental Health & Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom[*] Correspondence to: Mirza Faisal Beg, PhD, PEng, Michael Smith Foundation for Health Research Scholar, School of Engineering Science, Simon Fraser University, ASB 8857, 8888 University Drive, Burnaby, BC, Canada. Tel.: +1 778 782 5696; E-mail:[1] Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative database .

lyze novel biomarkers that can help predict the development and progression of DAT. Methods:We used feature selection and ensemble learning classifier to develop an image/genotype-based DAT score that represents a subject’s likelihood of developing DAT in the future. Three feature types were used: MRI only, genetic only, and combined multimodal data. We used a novel data stratification method to better represent different stages of DAT. Using a pre-defined 0.

 

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