Real-world applications in clinical documentation and trial matching
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There are a number of different ways that artificial intelligence (AI) may be coming into play in the field of oncology.
In a recent episode of the Cancer Advances podcast, Jame Abraham, MD, FACP, Chair of the Department of Hematology & Medical Oncology at the Cleveland Clinic Cancer Institute, joins podcast host Dale Shepard, MD, PhD, to share how AI can impact clinicians' work.
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Dale Shepard, MD, PhD: Can you highlight the things we're doing clinical trial basis. So, one of the hard parts about clinical trials is you see a patient in front of you and you say, "Well, I've got all these trials. What might my patient qualify for?" Maybe highlight a little bit about how we're trying to do trial matching activities.
Jame Abraham, MD: As all of us clearly understand, clinical trial is the gold standard of cancer treatment. And here, in the adults in the US, less than 10% of patients go on clinical trial. And that's due to many reasons. One reason is, as you said, it's so complex to understand the criteria, who meets the criteria, who doesn't meet the criteria.
So, the AI-based technology, Cleveland Clinic is partnering with a company to help us to identify patients who can potentially be eligible for certain trials. And they'll help the clinicians to cut through the noise and select the patients for the trial.
Dale Shepard, MD, PhD: And I guess the good part about that is some of these products, if someone might not have qualified because their white blood cell count was too low, it will go back and then tell you, if those numbers change, whether they're now eligible.
Jame Abraham, MD: Right. Which is huge.
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