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William F. Auffermann, MD, PhD

Languages spoken: English
  • William Auffermann M.D., Ph.D., currently serves as the Interim Section Chief for the Thoracic Imaging Section in the Department of Radiology and Imaging Sciences at the University of Utah. He is dual board certified in Diagnostic Radiology and Clinical Informatics. His research focuses on using our knowledge of medical image perception and perceptual errors to develop computer simulation based educational tools for medical image interpretation. This ongoing research project focuses on integrating human factors research/engineering with new simulation based methods for educating healthcare trainees and practitioners on the evaluation of diagnostic imaging studies. Human factors known to correlate with improved image interpretation and reduced diagnostic errors are incorporated into training algorithms using computer simulation. Subject performance improved as a function of training, with fewer diagnostic/medical errors. Using this paradigm, subjects were able to attain a higher level of proficiency at image interpretation, with fewer diagnostic/interpretive errors, in less training time that would be required for conventional educational methods. Additional research interests include: biomedical informatics, machine learning, structured reporting, and clinical decision support.

    Board Certification and Academic Information

    Academic Departments - Primary
    Academic Divisions
  • William Auffermann M.D., Ph.D., currently serves as the Interim Section Chief for the Thoracic Imaging Section in the Department of Radiology and Imaging Sciences at the University of Utah. He is dual board certified in Diagnostic Radiology and Clinical Informatics. His research focuses on using our knowledge of medical image perception and perceptual errors to develop computer simulation based educational tools for medical image interpretation. This ongoing research project focuses on integrating human factors research/engineering with new simulation based methods for educating healthcare trainees and practitioners on the evaluation of diagnostic imaging studies. Human factors known to correlate with improved image interpretation and reduced diagnostic errors are incorporated into training algorithms using computer simulation. Subject performance improved as a function of training, with fewer diagnostic/medical errors. Using this paradigm, subjects were able to attain a higher level of proficiency at image interpretation, with fewer diagnostic/interpretive errors, in less training time that would be required for conventional educational methods. Additional research interests include: biomedical informatics, machine learning, structured reporting, and clinical decision support.

    Board Certification and Academic Information

    Academic Departments -Primary
    Academic Divisions

    Education history

    Fellowship Cardiothoracic Radiology - Duke University School of Medicine Fellow
    Radiology - University of Minnesota Medical School Resident
    Internship Transitional Year - Hennepin County Medical Center Intern
    Medicine; Biomedical Engineering, Minor in Statistics - University of Minnesota Medical School M.D., Ph.D.
    Undergraduate Chemistry; Minor in Physics - Polytechnic University B.S.