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Critical imaging data fall through cracks in IT
Referring clinicians failed to acknowledge over one-third of abnormal imaging results in an outpatient setting, even when a computerized system designed to alert them was used, according to Dr. Hardeep Singh and colleagues at Baylor College of Medicine.
Referring clinicians failed to acknowledge over one-third of abnormal imaging results in an outpatient setting, even when a computerized system designed to alert them was used, according to Dr. Hardeep Singh and colleagues at Baylor College of Medicine.
Researchers analyzed 1017 outcomes of abnormal imaging alerts in an ambulatory multispecialty clinic that were transmitted to providers via the electronic medical record. Over one-third of these cases were not acknowledged by the referring clinicians, while 4% of critical imaging results remained unnoticed for about a month (J Am Med Inform Assoc 2007;14[4]:459-466).
MRI-Based AI Radiomics Model Offers 'Robust' Prediction of Perineural Invasion in Prostate Cancer
July 26th 2024A model that combines MRI-based deep learning radiomics and clinical factors demonstrated an 84.8 percent ROC AUC and a 92.6 percent precision-recall AUC for predicting perineural invasion in prostate cancer cases.
Breast MRI Study Examines Common Factors with False Negatives and False Positives
July 24th 2024The absence of ipsilateral breast hypervascularity is three times more likely to be associated with false-negative findings on breast MRI and non-mass enhancement lesions have a 4.5-fold likelihood of being linked to false-positive results, according to new research.
Can Polyenergetic Reconstruction Help Resolve Streak Artifacts in Photon Counting CT?
July 22nd 2024New research looking at photon-counting computed tomography (PCCT) demonstrated significantly reduced variation and tracheal air density attenuation with polyenergetic reconstruction in contrast to monoenergetic reconstruction on chest CT.
