Google builds AI that can predict heart disease

The Google AI Can Detect Heart Diseases In Eyes

"However, with medical images, observing and quantifying associations can be hard because of the wide variety of features, patterns, colors, values and shapes that are present in real images", researchers noted in a paper (PDF) published in the Nature journal Biomedical Engineering on Tuesday. Given the fact that heart diseases is one of the leading causes of deaths in the world, this algorithm could be a big breakthrough.

Google's parent company Alphabet has more than just the search giant under its banner; alongside its weird "X" experimental tech division sits its health science company Verily, which creates all manner of healthcare tech. "Our work also suggests avenues of future research into the source of these associations, and whether they can be used to better understand and prevent cardiovascular disease", conclude the authors of the study.

Further research will help determine whether the programme needs to be adjusted to analyse larger or smaller images, the website adds, while a "larger data set" would help improve the AI system's accuracy.

"They're taking data that's been captured for one clinical reason and getting more out of it than we now do", he said. According to USA Today, by looking at the images, 70% of the time Google's AI was able to accurately predict which patient would experience a heart attack or other major cardiovascular event within five years. Discovering that we could do this is a good first step.

In addition to predicting the various risk factors (age, gender, smoking, blood pressure, etc) from retinal images, our algorithm was fairly accurate at predicting the risk of a CV event directly.

Here are the changes Trump wants to make to food stamps program
USDA would likely not change that requirement but could grant states waivers to impose stricter requirements at the state level. Jason Kaplan, a spokesman for Sen. "It sets out to reduce hunger in the US and does extraordinarily well at it".

Coming soon.a Google AI heart disease test?! Results are most significant when the algorithm was tasked with determining specific risk factors.

In a paper published in Nature Biomedical Engineering, Google researchers, along with those from Verily Life Sciences and the Stanford School of Medicine, used deep learning algorithms trained on data from 284,335 patients.

"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.

"I am very excited about what this means for discovery", Peng said. In the future, doctors will be able to screen for the number one killer worldwide much more easily, and they will be doing it without causing us any physical discomfort.

However, if further studies do validate the findings, the use of retinal images could lower the barrier to doctors discussing preventative measures with a patient.

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