The content of this podcast is provided for general informational purposes only and is not intended as,

nor should it be considered a substitute for professional medical advice.

Hello, this is Karen Nicol family nurse practitioner, and you are listening to Itchy and Bitchy,

a podcast that provides answers to your many unanswered health questions.

In the last episode, I shared the good, the bad, and the ugly of digital health. And I promise to you that I would help you

understand how AI is being used in healthcare in this episode. So here we go. A.I. Artificial

intelligence are intelligent machines through a set of rules mimic human cognitive functions such as learning and

problem solving. These machines have the potential to anticipate problems or deal with issues as they

come up and so they function in an intelligent and adaptive manner. In addition, they learn and adapt as more data become available.

Its ability to learn patterns and relationships from enormous databases is the strength of AI.

For an example of how this can work in medicine, AI can review a patient's entire medical record and translate the information

into a single number that represents a likely diagnosis. So there are some key applications

and examples of AI in medicine. I am sure you know much about AI in other areas of life, but I'm going to be talking about

what is used and how it's used in medicine. Abnormalities in x-rays, MRIs, and CT scans can be

detected by AI with high precision. It functions as a powerful automated assistant for radiologists using machine

learning to analyze and interpret scans like MRIs, CTs, and x-rays with high speed and precision.

It detects subtle, early stage abnormalities such as tumors, fractures, or neurologic changes

that might be missed by the human eye, therefore improving diagnostic accuracy.

AI is also being used during colonoscopy procedures, providing assistance in real time. By analyzing live video, the use of AI can boost

polyp detection rates by 20 to 44%. Trained on millions of images, the algorithm used this deep learning

to highlight precancerous lesions with colored boxes,

so the doc can see it, and this aids the doc's ability to identify flat, small, or hidden polyps.

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