title: CADe for early detection of breast cancer-current status and why we need to continue to explore new approaches.
abstract: The authors describe where we are in terms of using computer-aided detection (CADe) systems during clinical mammographic interpretations, what are the issues that we face, and why they believe that, despite disappointment in terms of verified added value when it comes to detection of soft tissue abnormalities, we need to continue to explore new approaches to improving CADe-alone performance levels and, more important perhaps, new approaches to optimal communication of CADe-generated information.
authors.affiliation: Imaging Research, Department of Radiology, University of Pittsburgh, 3362 Fifth Ave, Pittsburgh, PA 15213. Electronic address: nishikawarm@upmc.edu.
authors.forename: Robert M
authors.initials: RM
authors.lastname: Nishikawa
authors.affiliation: Imaging Research, Department of Radiology, University of Pittsburgh, 3362 Fifth Ave, Pittsburgh, PA 15213.
authors.forename: David
authors.initials: D
authors.lastname: Gur
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001943:Breast Neoplasms / Q000175:diagnosis*; D055088:Early Detection of Cancer / Q000639:trends*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008327:Mammography / Q000639:trends*; D008403:Mass Screening / Q000639:trends*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: Computer-aided detection; breast imaging; computer-aided diagnosis; mammographic screening