Nardeth
Senior Member
Scientists from Google and its health-tech subsidiary Verily have discovered a new way to assess a person's risk of heart disease using machine learning.
By looking at the human eye, Google's algorithms were able to predict whether someone had high blood pressure or was at risk of a heart attack or stroke, Google researchers said Monday, opening a new opportunity for artificial intelligence in the vast and lucrative global health industry.
The algorithm potentially makes it quicker and easier for doctors to analyze a patient's cardiovascular risk, as it doesn't require a blood test. But, the method will need to be tested more thoroughly before it can be used in a clinical setting. A paper describing the work was published today in the Nature journal Biomedical Engineering, although the research was also shared before peer review last September.
"Using deep learning algorithms trained on data from 284,335 patients, we were able to predict CV risk factors from retinal images with surprisingly high accuracy for patients from two independent data sets of 12,026 and 999 patients," Lily Peng, MD, product manager and a lead on these efforts within Google AI, wrote in the Google AI official blog.
"For example, our algorithm could distinguish the retinal images of a smoker from that of a non-smoker 71 percent of the time, compared to a ~50 percent (i.e. random) accuracy by human experts," she said.
Read More Here
https://www.speedguide.net/news/google-ai-can-predict-heart-disease-6617
By looking at the human eye, Google's algorithms were able to predict whether someone had high blood pressure or was at risk of a heart attack or stroke, Google researchers said Monday, opening a new opportunity for artificial intelligence in the vast and lucrative global health industry.
The algorithm potentially makes it quicker and easier for doctors to analyze a patient's cardiovascular risk, as it doesn't require a blood test. But, the method will need to be tested more thoroughly before it can be used in a clinical setting. A paper describing the work was published today in the Nature journal Biomedical Engineering, although the research was also shared before peer review last September.
"Using deep learning algorithms trained on data from 284,335 patients, we were able to predict CV risk factors from retinal images with surprisingly high accuracy for patients from two independent data sets of 12,026 and 999 patients," Lily Peng, MD, product manager and a lead on these efforts within Google AI, wrote in the Google AI official blog.
"For example, our algorithm could distinguish the retinal images of a smoker from that of a non-smoker 71 percent of the time, compared to a ~50 percent (i.e. random) accuracy by human experts," she said.
Read More Here
https://www.speedguide.net/news/google-ai-can-predict-heart-disease-6617