Category: Radiology Software

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Ensembling Improves Machine Learning Model Performance

Ensembles created using models submitted to the Radiological Society of North America Pediatric Bone Age Machine Learning Challenge convincingly outperformed single-model prediction of bone age, according to a study published in the journal Radiology: Artificial Intelligence.

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Mission Accomplished

Mike Ryan at the Veterans Affairs (VA) Midwest Healthcare Network—also known as VISN23—is proud of his team’s work on deploying a “deconstructed PACS” across the network’s 11 facilities. Still, Ryan, who is informatics coordinator of the imaging service line, would rather talk about the honor of working with his fellow VA employees to “serve those who have served.”

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