Indian Scientists Developing Smart Diagnostics System To Predict Alzheimer?s Disease Early

In a research breakthrough, Indian scientists are using artificial intelligence to predict Alzheimer’s disease early.

There is good news coming out in the area of Alzheimer’s Disease research. Alzheimer’s is the most common form of dementia and a progressive degenerative brain disorder. It is irreversible and can impair a person’s cognitive behaviour and daily living. Now scientists in India are using artificial intelligence (AI) to develop a smart diagnostics system that can predict Alzheimer’s disease early.

Early detection of Alzheimer’s disease can help individuals achieve better quality of life by identifying the cognitive impairment and taking preventive measures to slow down the process. It can also lead to more appropriate treatment.

In a report published in the Journal of Alzheimer’s Disease, Professor Pravat Mandal and other noted scientists from the National Brain Research Centre (NBRC), Gurugram and Neuroimaging and Neurospectroscopy Laboratory (NINS) are together working towards this. They are developing a model to map metabolic patterns in different brain regions in healthy and pathological conditions.

Alzheimer’s disease accounts for 60 to 80 percent of dementia cases. The greatest known risk factor is increasing age, and the majority of people with Alzheimer’s are 65 and older. According to the ‘Dementia India’ report published by the Alzheimer’s and Related Disorders Society of India (ARDSI), India has an estimated 4.1 million people suffering from dementia, a number expected to double by 2035.

“Laboratory research and longitudinal clinical studies have helped to reveal various information about the disease but the exact causal process is not known yet. Patterns from alteration of neurochemicals, hippocampal atrophy, and brain effective connectivity loss as well as associated behavioural changes have generated important characteristics features. These imaging-based readouts and neuropsychological outcomes along with supervised clinical review are critical for developing a comprehensive artificial intelligence strategy for early predictive AD diagnosis and therapeutic development,” Dr Mandal wrote in the Journal.

He also mentioned using the data information from a large data set from various diagnosis procedures to create an artificial intelligent system, which would help with the diagnosis of a new unknown case of Alzheimer’s disease using machine learning approaches. “Such an integrated multi-modal predictive diagnostic system for Alzheimer’s disease diagnosis would aid the clinician in early differential diagnostics to deliver the most appropriate treatment,” he said.

Dr Mandal and Deepika Shukla of NBRC are developing an integrated framework called GAURI with statistical and predictive diagnostic capability that could indicate chemical changes in the human brain. Alzheimer’s Disease can lead to not just cognitive impairment but also affect the life of the person and others around him. A breakthrough in early prediction can result in not only better focused treatment but also improved care and life condition for both the person with Alzheimer’s and the caregiver.