Key points are not available for this paper at this time.
In radiology, as in various other fields, observers study images to detect and diagnose underlying conditions. They make assessments of several image features and merge them into an overall decision. Demonstration is given here, in the context of mammography, that objective aids to this interpretative process can substantially improve accuracy, even for sophisticated and motivated radiologists. The aids are a checklist that solicits explicit, quantitative, systematic assessments of the important features of an image and a computer program that merges those assessments with optimal weights. The computer issues estimates of the likelihoods that specified conditions are present (in this study, the likelihood that a localized abnormality is malignant), and the radiologist benefits from taking those estimates as guidance.
Getty et al. (Fri,) studied this question.