Today, I want to take a look at the research on using deep learning and artificial intelligence to make early diagnoses of eye conditions by analyzing images of the retina. This technology can identify diseases like macular degeneration and diabetic retinopathy, and may even indicate risks of cardiovascular issues and early-stage dementia. Enjoy the show!

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Referenced Article: Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning

SUMMARY KEYWORDS

retina, deep learning, researchers, disease, deep learning model, eye, podcast, diagnosis, macular degeneration, eye exam, degeneration, capillaries, early, artificial intelligence, biological, level, macula, micro, early diagnosis, clarity

00:06

Hey everybody, its Dr. Sam and I’d like to welcome you to my EyeClarity podcast. If you want to get in touch with me with questions, you can email me at [email protected]. And you can always text me your questions at 1-844-932-1291. I would like to let you know about my new membership program. This is going to offer members new information on how to improve their vision and wellness. So you will get access to articles, video, blogs, podcasts, and webinars. Also a live Q&A with me. And all of this information will empower you to make informed decisions about your vision, and your health. So to sign up to go to my website, drsamberne.com. And you can see the details there. All right now on to the show.

01:36

Hey, everybody, its Dr. Sam, I’d like to welcome you to our EyeClarity podcast today. So I want to bring in some interesting research. And it has to do with being able to make an early diagnosis of eye conditions. And once you have that diagnosis, you can then use proactive or preventative ways to either slow down the progression, and in some cases, even reverse the disease process. So there’s a new type of research out there called deep learning this is done through artificial intelligence. And researchers are using pictures of the retina cells. It’s the micro capillaries, the optic nerve, the macula.

And when you go for an eye exam, either the eye doctor looks with a some kind of a scope at your retina back of your eye. Or he or she now can use a photography instrument to take a measurement of the status of your retina cells, your macula, your optic nerve, and so on. So in this next level of diagnosis, what researchers are doing is they are calculating your biological age, using what we call deep learning models. And this is an artificial intelligence process.

Whereby what happens is the researchers have hooked into a very large database of pictures of the eye. And these images show different stages of the diagnosis, diseases, especially in the areas of macular degeneration, diabetic retinopathy. And you know, in other podcasts, I’ve talked about how eye doctors can look at the retina, because it’s such a great window into the body. And they can even pick up the brain health. So early stages of dementia, and even cardio vascular disease because when you look at the retina, you’re looking at the health of the tiniest blood vessels that are in the body, which we call the micro capillaries. And I’ve talked about them a lot because the micro capillaries are key in your ability to oxygenate and hydrate the tissue in the back of the eye. And when there’s a starvation when there’s oxidative stress when there’s inflammation in these micro capillaries, this is when disease starts to occur.

So in this biological age that the researchers are looking at, if they can tell early on that there might be some deterioration and this is detected through through this deep learning artificial intelligence, because with the database that the researchers have collected, they now know what are the patterns? What, what are the images looking like, on a very subtle level, if you start showing, say, macular degeneration, and the ability for this deep learning AI to, to diagnose is so much better than even well trained ophthalmologist or optometrist who does an eye exam. Now, let’s say in this model, that there’s an early diagnosis of, say, macular degeneration, you can then modify your health practices, change your lifestyle, change your diet, maybe do some of the things that I suggest to recommend, and you are really catching the the the disease very early.

So this biological clock that is being recognized by this deep learning model is really a breakthrough in one’s ability to be able to diagnose very early on. And in fact, some of the researchers have talked about actually creating an app where lay people can take a photograph of their eye, and they can send it somewhere a database. And they can actually get some results to see whether or not this biological age estimation is showing some type of disease process.

And in being able to predict retinal disease risk, you know, things like, again, diabetic retinopathy, glaucoma, macular degeneration. In this deep learning technology, the earlier detection and diagnosis is much sooner than what you would get even if you went for a regular eye exam. And what I’m really intrigued about this is that the deep learning artificial intelligence program is able to analyze these retinal features associated with the disease progression in such a minut and very specific way.

And so then you get to see, okay, what’s the biological age estimation? What’s the prediction, when somebody could lose their eyesight, or even you can even see things like morbid morbidity, risks, because in part of the pictures of the retina, when you look at the micro capillaries, you can actually begin to see oh, there may be problems on a cardiovascular level, and even on a brain level that there may be problems with early stages dementia.

So I will put a link to one of the journal articles that I was reading about this deep learning artificial intelligence and photographing the retina, and being able to make an earlier detection of eye disease. And then with that, applying some of my alternative or holistic methods that can help slow down or even in some cases, reverse some of the degeneration. To me, that sounds like a no brainer. That is going to be a really great technology, as the researchers continued to do more and more work on it. So that’s our show for today. I want to thank you so much for tuning in. And until next time, take care.

08:54

Thank you for listening. I hope you learned something from the EyeClarity podcast show today. If you enjoyed the episode, make sure to subscribe on iTunes or Spotify and leave a review. See you here next time.