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posted by janrinok on Tuesday February 27 2018, @05:03PM   Printer-friendly
from the keeping-an-eye-on-things dept.

The idea behind using a neural network for image recognition is that you don't have to tell it what to look for in an image. You don't even need to care about what it looks for. With enough training, the neural network should be able to pick out details that allow it to make accurate identifications.

For things like figuring out whether there's a cat in an image, neural networks don't provide much, if any, advantages over the actual neurons in our visual system. But where they can potentially shine are cases where we don't know what to look for. There are cases where images may provide subtle information that a human doesn't understand how to read, but a neural network could pick up on with the appropriate training.

Now, researchers have done just that, getting a deep-learning algorithm to identify risks of heart disease using an image of a patient's retina.

The idea isn't quite as nuts as it might sound. The retina has a rich collection of blood vessels, and it's possible to detect issues in those that also effect the circulatory system as a whole; things like high levels of cholesterol or elevated blood pressure leave a mark on the eye. So, a research team consisting of people at Google and Verily Life Sciences decided to see just how well a deep-learning network could do at figuring those out from retinal images.

Source: https://arstechnica.com/science/2018/02/ai-trained-to-spot-heart-disease-risks-using-retina-scan/


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  • (Score: 0) by Anonymous Coward on Tuesday February 27 2018, @06:35PM

    by Anonymous Coward on Tuesday February 27 2018, @06:35PM (#644714)

    This is the road to Skynet.

  • (Score: 2) by Dr Spin on Tuesday February 27 2018, @08:37PM

    by Dr Spin (5239) on Tuesday February 27 2018, @08:37PM (#644779)

    If there is a cat in my retina, I need to know about it!

    --
    Warning: Opening your mouth may invalidate your brain!
  • (Score: 0) by Anonymous Coward on Tuesday February 27 2018, @09:03PM (2 children)

    by Anonymous Coward on Tuesday February 27 2018, @09:03PM (#644800)

    still not clear what the risk to the ái is. that would be more interesting.

    still, I have a rock outside my kitchen that can identify current weather conditions. If it's wet it is probably raining.

    The point of that keen observation is this exam technique seems only to confirm what the clinician can probably guess at within a few minutes with a new patient. Overweight? high bp? skinny, but bulging carotid arteries or juglar veins? smells like an ashtray? bad breath (gum disease indicator)? funky finger nails? clubby finger tips? slow perfusion?

    ok lets run a few tests just to confirm....

    because insurance reimburses for tests and procedures, not observational notes.

    • (Score: 2) by DannyB on Tuesday February 27 2018, @10:36PM (1 child)

      by DannyB (5839) Subscriber Badge on Tuesday February 27 2018, @10:36PM (#644843) Journal

      > AI Trained to Spot Heart Disease, Risks Using Retina Scan

      Why would an AI risk using a Retina Scan when there are less risky ways to detect heart disease?

      It all depends on where you put the comma.

      Headlines, especially at Ars, are becoming more difficult to parse. Maybe need a different parser generator. Or a better headline generator.

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      • (Score: 2) by Osamabobama on Tuesday February 27 2018, @10:57PM

        by Osamabobama (5842) on Tuesday February 27 2018, @10:57PM (#644851)

        AI Trained to Spot Heart Disease Risks by Using Retina Scan

        Three additional characters. I can do better...

        AI Detects Heart Disease with Retina Scan

        A little shorter, but perhaps more confusing.

        AI Finds Heart Disease in Eye

        I think I'm done here.

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        Appended to the end of comments you post. Max: 120 chars.
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