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Biomarker model predicts breast cancer risk without racial bias

AuntMinnie

Lamb and colleagues sought to assess the performance of an image-based deep learning risk assessment model for predicting both future invasive breast cancer and ductal carcinoma in situ (DCIS) across multiple races. Image and caption courtesy of RSNA. for White women, with lower performance in women of other races.

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Synoptic Reporting Improves Pretreatment CT for Advanced Ovarian Cancer

Imaging Technology

An ovarian cancer synoptic report increased completeness of reporting, facilitating referrer communication and having the potential to improve clinical decision-making,” wrote first author Pamela Causa Andrieu, MD , from the department of radiology at Memorial Sloan Kettering Cancer Center in New York City. Andrieu et al.’s Andrieu et al.’s

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ChatGPT identifies incidental CT findings

AuntMinnie

While it’s common for clinically important incidental imaging findings to be reported, they can be overlooked or not managed properly. For their study, the researchers tested ChatGPT-4’s performance with single-shot learning for identifying incidental findings in radiology reports, which contain medical jargon.