Artificial Intelligence shows how Alzheimer’s, diabetes and schizophrenia affect the brain
According to a study by the University of Koimbra, according to a study by the University of Coimbra, Alzheimer’s disease reveals that the brain is the age of nine years beyond the age of nine years of age, five -year -olds of Type 2 diabetes and five -year -old schizophrenia.
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“Using Artificial Intelligence Techniques and various databases around the local and worldwide, which is possible Separate the biological era of chronologicalIt refers to a new look Measure the effect of these chronic diseases – directly or indirectly – affecting the brain“, UC said in Communication.
The study pointed out, “In the case of Alzheimer’s disease, old age can reach over nine years than the real age of the patient”.
Biomedical Image Center and Translation Researcher Maria Fatima Dias at the UC and the Center for Informatics and Systems of the Koimbra’s Institute of Nuclear Sciences, the first author and teachers and researchers of this study were guided by Miguel Costello-Branco and Palo de Carlolho.
“The brain is provided by the biological age of the brain, the biological age of the brain, which is provided by the brain images. Its chronological (the actual age of a person, measured in the years) allows the brain to indicate that the brain is more or less or lesser than the exposed.”
According to the researcher, “The positive value of ‘brain age gap’ means rapid brain aging, but negative value is an indicator of the cerebellum from the biological point of view, with retarded aging”.
Using various samples of artificial intelligence, obtained Maps that allow brain to understand that the biological era has contributed to the calculation. Dimensions are also established The average effect of each disease on brain aging.
“In the case of schizophrenia, brain aging is about two years, Type 2 diabetes will reach five years and Alzheimer’s disease,” the researcher said.
For Miguel Costello-Branco, resolutions taken from this study can open new ways: “It is possible to use this measurement as a useful biomarker in the early diagnosis of neurodegenerative diseases.”
The study includes the UC’s Medicine Faculty of Medicine, Biomedical Image Center and Translational Research, Institute of Nuclear Sciences Health, Center for Informatics and Systems of UC and Associated Laboratory.
