Tuesday November 13, 2018

New AI Model to Identify the Risk of Heart Disease in Indians

Besides Apollo, Microsoft is also planning to extend the AI model to other healthcare providers

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Lead, mercury exposure raises cholesterol levels: Study. Pixabay
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In a novel effort to predict the risk of cardiovascular disease (CVD) among the Indian population, Microsoft India and Apollo Hospitals on Friday launched the first-ever Artificial Intelligence (AI)-powered heart disease risk score API (application programme interface).

Part of Microsoft’s “AI Network for Healthcare” initiative, it will help doctors across the Apollo network of hospitals leverage the AI-powered API to predict risk of CVD and drive preventive cardiac care across the country.

Nearly three million heart attacks happen in India every year and 30 million Indians suffer from coronary diseases. However, even with various heart disease risk models available worldwide, doctors and cardiologists are unable to identify the probability of CVD in Indians.

“The AI-based models available worldwide were formed decades ago and are based on the western population. Our new API score is based on the data of 4,000 Indians shared by Apollo Hospitals and can easily identify the level of risk each patient has,” Anil Bhansali, Managing Director, Microsoft India (R&D), told IANS.

“We come in as a technology partner or expert in the AI domain, where we collaborate with healthcare providers and doctors to integrate data to help build the AI model,” Bhansali added.

Built on Microsoft’s Cloud computing platform Azure, the new AI-based heart risk score helps gauge a patient’s risk for heart disease and provides rich insights to doctors on treatment plans and early diagnosis.

The API score considers 21 risk factors including lifestyle attributes such as diet, tobacco and smoking preferences and physical activity as well as psychological stress and anxiety as reflected via rate of respiration, hypertension and systolic and diastolic blood pressure.

“The score categorises risk into high, moderate and minimal and also provides insights on the top modifiable risk contributors, thereby assisting physicians to consult patients in a more holistic way, while providing insights to patients for lifestyle modification and timely interventions,” Bhansali elaborated.

heart disease
Representational image. (IANS)

When a patient goes for a cardio health check, the doctor can build up a more accurate cardio-vascular health profile of the patient based on Machine Learning (ML) of all their previous patient data.

AI can, in turn, predict future coronary ailments the patient might experience in the next 10 to 20 years based on these multiple factors.

“This heart risk score for Indian populace is a true example of how precision healthcare can accelerate prevention of cardio-vascular disease and reduce disease burden,” Bhansali noted.

According to Sangita Reddy, Joint Managing Director, Apollo Hospitals, the partnership is aimed at designing new tools and equip doctors in the fight against non-communicable diseases.

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“The amalgamation of AI and ML with the global expertise of our doctors will help prevent heart disease, save lives and ensure those with heart disease can make informed choices on their health,” Reddy said in a statement.

Besides Apollo, Microsoft is also planning to extend the AI model to other healthcare providers.

“While we are currently working with Apollo, we are also in the process of identifying partners where we can actually try this API score,” Bhansali told IANS.

“In the last couple of years we have been working on how Cloud technology, particularly AI, can help in reducing the overall disease burden. Our first step towards this, as part of the healthcare partnership, is developing the cardiac risk score for Indian population,” Bhansali added. (IANS)

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AI Technique to Improve Brain Scans to Predict Alzheimer’s Early

"If we diagnose Alzheimer's disease when all the symptoms have manifested, the brain volume loss is so significant that it's too late to intervene," Sohn said

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AI technique can boost brain scans to predict Alzheimer early. Pixabay

Artificial intelligence (AI) can help improve the ability of brain imaging techniques to predict Alzheimer’s disease early, according to a study.

Researchers from the University of California in San Francisco (UCSF) trained a deep learning algorithm on a special imaging technology known as 18-F-fluorodeoxyglucose positron emission tomography (FDG-PET).

They included more than 2,100 FDG-PET brain images from 1,002 patients and on an independent set of 40 imaging exams from 40 patients.

The results showed that the algorithm was able to teach itself metabolic patterns that corresponded to Alzheimer’s disease.

It also achieved 100 per cent sensitivity at detecting the disease an average of more than six years prior to the final diagnosis.

“We were very pleased with the algorithm’s performance. It was able to predict every single case that advanced to Alzheimer’s disease,” said Jae Ho Sohn, from UCSF’s Radiology and Biomedical Imaging Department.

“If FDG-PET with AI can predict Alzheimer’s disease this early, beta-amyloid plaque and tau protein PET imaging can possibly add another dimension of important predictive power,” he added, in the paper detailed in the journal Radiology.

While early diagnosis of Alzheimer’s is extremely important for the treatment, it has proven to be challenging.

"The question for us now is not how to eliminate cholesterol from the brain, but about how to control cholesterol's role in Alzheimer's disease through the regulation of its interaction with amyloid-beta," Vendruscolo said.
The results showed that the algorithm was able to teach itself metabolic patterns that corresponded to Alzheimer’s disease, Pixabay

Although the cause behind the progressive brain disorder remains unconfimed yet, various research has linked the disease process to changes in metabolism, as shown by glucose uptake in certain regions of the brain.

These changes can be difficult to recognise.

“If we diagnose Alzheimer’s disease when all the symptoms have manifested, the brain volume loss is so significant that it’s too late to intervene,” Sohn said.

Also Read- Eat Vegetarian Diet to Ward Away Heart Disease

“If we can detect it earlier, that’s an opportunity for investigators to potentially find better ways to slow down or even halt the disease process,” he noted.

Sohn explained that the algorithm could be a useful tool to complement the work of radiologists — especially in conjunction with other biochemical and imaging tests — in providing an opportunity for early therapeutic intervention. (IANS)