Is Artificial Intelligence the Silver Bullet for Heart Disease?

Cardiovascular disease is the leading cause of death globally. According to the World Health Organization, approximately 31% of all global deaths occur due to cardiovascular diseases (CV) diseases, with coronary heart disease being the most common type. Four out of five CV disease deaths are due to heart attacks and strokes.

However, early detection, and preventive measures and management including lifestyle and diet modification and proper treatment for CV diseases can significantly reduce morbidity and mortality. Meanwhile, researchers are developing tools to help identify the probability of CV diseases, harnessing the power of artificial intelligence (AI).

The pharma/biotech industry has started adopting AI, the simulation of human intelligence processes by machines, especially computer systems, albeit slowly. It is touted as the next big thing in the biotech industry as it can drastically reduce time and costs involved in developing life-saving drugs.

Artificial intelligence driven solutions can enable pharma/biotech companies to identify the appropriate patient population, reduce or eliminate the need for some studies, and in some cases even predict outcomes in a virtual patient. Many technology companies such as International Business Machines Corporation IBM, Apple AAPL, and Google are investing heavily in AI and machine-based applications to facilitate precision medicine.

Artificial intelligence based on machine learning can play an important role in predicting heart attacks and other cardiac events and monitoring CV diseases. It can empower doctors with the power of data to make better clinical decisions. The first applications of AI in the cardiovascular field are promising. AI and machine learning-based applications like cardiac computed tomography angiography imaging tests are helping doctors see images of patients’ coronary arteries/blood vessels and preventing invasive tests. Researchers at the University of Oxford have developed a new machine learning based technology, a biomarker or 'fingerprint' called the fat radiomic profile to predict an impending heart attack with greater precision. The researchers claim that this technology can identify people at risk of a heart attack five years in advance.

A few global collaborations have been formed in the past couple of years between big pharma/biotech players and small AI-driven companies, primarily startups, to discover novel biological targets and molecules for treating CV diseases using AI.

In August, Sensyne Health, a British AI technology company, signed a two-year collaboration deal with Germany-based drug giant Bayer BAYRY to identify new treatments for heart diseases using Sensyne’s proprietary clinical AI technology platform. Bayer currently carries a Zacks Rank #3 (Hold). You can see the complete list of today’s Zacks #1 Rank (Strong Buy) stocks here.

In March last year, Microsoft MSFT announced collaboration with India’s Apollo Hospitals to use its path-breaking AI and machine learning technologies for early detection of cardiac diseases.

Though the use of AI for predicting and monitoring heart diseases is in relatively early stages, a broad-scale adoption is expected in the next five years.

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