How Big Data Is Curing Alzheimer’s Disease?
Nearly 44 million people around the world are diagnosed with Alzheimer’s disease. Though there is an array of robust technologies for prior detection of deadly diseases, identifying neurodegenerative disorders, such as Alzheimer’s disease is no mean feat. In this case, advanced developments in the world of medicine are of little help.
Nevertheless, a crop of talented Indian researchers has found a way to apply big data analytics to seek early signs of Alzheimer’s in the patients. They belong to the National Brain Research Centre, Manesar and they have devised an incredible big data analytics framework that leverages non-invasive imaging and several other test data to identify diagnostic biomarkers visible in the prior stages of the disease.
The Hadoop-powered data framework incorporates data right from the brain in the natty format of non-invasive tests — magnetic resonance spectroscopy (MRS), magnetic resonance imaging (MRI) and neuropsychological test results — by taking suave advantage of data mining, machine learning and statistical modeling algorithms, distinctively. Addressing the big three Vs — Volume, Variety and Velocity, the framework developed on cutting-edge machine learning analyzes humongous volumes of data derived from brain scans conducted with the help of MRI or MRS. This is simply not possible alone with human intelligence.
For more, hit the link — www.dexlabanalytics.com/blog/big-data-to-cure-alzheimers-disease
The research conducted is in association with Ministry of Department of Science and Technology and it includes honorable members, such as Dr Mandal, Dr Deepika Shukla, Ankita Sharma and Tripti Goel.
In case, if you want to know more about the machine learning course in India, reach us at DexLab Analytics.
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