Amazing: AI algorithm by Google which can detect heart disease

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The AI algorithms need a good dose of machine learning before they can do this well, which involved analysing a medical dataset of around 300,000 patients and crunching both eye scans and more general medical data.

"Recently, we've seen many examples of how deep learning techniques can help to increase the accuracy of diagnoses for medical imaging, especially for diabetic eye disease", Peng explained.

The retinal fundus image includes blood vessels of the eye, which the paper shows can be used to accurately predict cardiovascular risk factors, including whether a person is smoker, blood pressure, age, gender, and whether a person has had a heart attack.

According to the Centers for Disease Control and Prevention, around 610,000 people die of heart disease in the United States every year, and 370,000 of these deaths are due to coronary heart disease (CHD).

Technology has not stopped unbelievable us and so has not Google. In doing so, Google Retinal Scans Uses AI To Determine Heart Attack Risks.

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Currently, when doctors assess risk for cardiovascular disease, they take into account information such as age, sex, smoking, blood pressure and cholesterol levels from a blood test. While the link between the eyes and the heart may be somewhat well-known, no human could ever hope to study enough pairs of peepers to actually figure out what all of the different properties of the eye meant as far as heart disease risk. The discovery may point to more ways to diagnose health issues from retinal images, researchers said.

The research, one of an increasing number of conceptual health-technology studies, was conducted by Google and Verily Life Sciences, a subsidiary of Google's parent Alphabet.

In addition, while doctors can typically distinguish between the retinal images of patients with severe high blood pressure and normal patients, the algorithm could go further to predict the systolic blood pressure within 11 mmHg on average for patients overall, including those with and without high blood pressure. This can give clinicians greater confidence in the algorithm, and potentially provide new insights into retinal features not previously associated with cardiovascular risk factors or future risk. The algorithm could predict the heart attacks and cardiovascular events, 70 percent of the time, the researchers noted. Importantly it makes quicker and easier analysis of a patient's cardiovascular risk since it doesn't require a blood test.

Google also made sure to determine how the algorithm was making its prediction. "This could help scientists generate more targeted hypotheses and drive a wide range of future research", researchers added.

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