Role of AI in Diagnosing Alzheimer's and Heart Attacks

By CIOReview | Friday, July 19, 2019

With AI, symptoms for Alzheimer's disease and heart attacks can be easily identified.

FREMONT, CA- As indicated by the World Health Organization (WHO), around 50 million individuals on the planet have dementia. Doctors have diagnosed dementia in approximately 10 million individuals consistently, and about 60–70 percent of these new diagnoses are recognized as Alzheimer's disease (AD). Out of these, only 15-16 percent receives regular cognitive testing. Since more instances of this disease are recorded, it is crucial to make diagnosis simpler.

Online memory test like MemTrax is a way to diagnose Alzheimer's disease, but its functioning has not been validated and demonstrated sufficiently. Different complicated and interdependent factors must be considered when interpreting the outcomes of the memory assessment test, so the job becomes tough for clinicians. Researchers have deployed novel applications of supervised machine learning and artificial intelligence to demonstrate and validate the utility of online memory test. artificial intelligence (AI) enhances brain imaging's capacity to predict Alzheimer's illness.

Machine learning has an intrinsic ability to uncover significant trends and perspectives from a comprehensive, complicated interdependent set of clinical determinants and the ability to learn from the continuing usefulness of practical predictive models.

According to a report published in Radiology, when machine learning is used with periodic heart scanning, better outcomes are obtained in anticipating heart attacks and other heart occurrences than with standard risk models. Heart illness is a vital cause of death for both men and women in the United States. Early intervention, in terms of diet, exercise, and suitable drugs, can significantly reduce the risk, making it essential to assess that risk. However, risk determination in the diagnosis of Alzheimer's disease is as imperfect as memory evaluation exams. Many traditional ways of diagnosis for heart illness and, Alzheimer's disease is limited. With AI and ML new hopes are being developed to find help prevent these disease.

Helping clinicians find a better way to apply and interpret memory assessment tests is extremely crucial, as this would ensure that more people are tested , thereby preventing the Alzheimer's disease and better manage the illness.

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