Dr. Ramsey Wehbe, a cardiologist and postdoctoral fellow in A.I.[1]Wehbe is a postdoctoral fellow at Bluhm Cardiovascular Institute at Northwestern Memorial Hospital.[2]Wehbe, MD, in the midst of our Northwestern Medicine Fellowship in Artificial Intelligence in Cardiovascular Disease, recently published a paper with impressive results from a set of 5,853 patients using machine learning to accurately identify COVID-19 using chest X-rays.[3]Wehbe and his colleagues expect the system to save not just on time but the costs associated with employing radiologists to identify potential COVID-19 patients.[4]
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Researchers at Northwestern University have developed DeepCOVID-XR, an AI platform for detecting COVID-19 from X-ray images of the lung. The researchers developed, trained and tested the system with 17,002 chest X-ray images, which they say is the largest published clinical dataset of chest X-rays during COVID-19 for training an AI system. Wehbe and his colleagues expect the system to save not just on time but the costs associated with employing radiologists to identify potential COVID-19 patients.[4]
12/07/2020
The panel said a lack of transparency surrounding the datasets that train algorithms can lead to public mistrust in AI-powered medical tools, as these devices may not have been trained using patient data that represents the patients on which they will be used.[3]
11/30/2020
Faster, earlier detection of the highly contagious virus could potentially protect health care workers and other patients by triggering the positive patient to isolate sooner. The study's authors also believe the algorithm could potentially flag patients for isolation and testing who are not otherwise under investigation for COVID-19. Katsaggelos' laboratory specializes in using A.I. for medical imaging. He and Wehbe had already been working together on cardiology imaging projects and wondered if they could develop a new system to help fight the pandemic.[2]
11/24/2020