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- W2940198103 abstract "Age Prediction, which means setting up a machine learning system, defined by using different sets of data for training, and then the estimation of the actual age of humans, is a subject that has been studied in recent years. To achieve this, researchers have been experimenting with various body components, such as DNA, speech signals, medical images, facial images, etc. Recent researches show that brain structure changes with age or psychiatric disorders. So a useful tool for estimating the age of humans is the brain’s MRI images. Brain Magnetic Resonance Imaging (MRI) use radio waves and a robust magnetic field to create detailed images of the organs and tissues within the body. In this paper, the age of humans is predicted based on brain MRI images. To extract T1-MRI features, two different methods are proposed, then to estimate age, Extreme Learning Machine (ELM) is employed. Given that the amount of computations needed in this method and the time required to age estimation is low, the proposed method has acceptable performance." @default.
- W2940198103 created "2019-04-25" @default.
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- W2940198103 date "2019-01-01" @default.
- W2940198103 modified "2023-09-26" @default.
- W2940198103 title "Age Prediction based on Brain MRI Images using Extreme Learning Machine" @default.
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- W2940198103 doi "https://doi.org/10.1109/cfis.2019.8692156" @default.
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