Profile

• What is the best web address for people to learn more about you?

  http://www.ucair.med.utah.edu/FacultyChapman/Chapman.html

  
  
• What would you like us to know about you?

  I have a PhD in biomedical informatics with a BS and MS in Electrical Engineering. I have held faculty appointments in internal medicine, biomedical informatics, bioengineering, and radiology departments. Since October 2013 I have been at the University of Utah where I am an associate professor of Radiology and am partially funded by the Vice President for Health Sciences to develop interdepartmental biomedical informatics initiatives. This work extends on the informatics education that I have focused on for the past 15 years. Biomedical informatics is an inherently multi-disciplinary professional, drawing upon multiple domains including medicine, biology, computer science, engineering, and mathematics. The very breadth of biomedical informatics creates unique challenges in both education and research as few individuals have knowledge and skills from all the relevant disciplines. A primary objective for me is increasing the mathematical literacy of biomedical scientists. As such I have developed and taught courses in mathematical foundations of biomedical informatics, organized a workshop on mathematical modeling in the health sciences, and submitted R25 proposals for short-term training for biomedical scientists in big data. My research addresses two fundamental questions in medical imaging: 1) the formalization of medical imaging (e.g., making medical images computable by extracting quantitative features from them) and 2) improving information flow into and out of radiology (e.g., by creating structured radiology reports and measuring information content and quality of radiology reports). With the formalization of medical imaging, we are developing tools for automated segmentation of multiple organ systems from large collections of images, creating statistical atlases from these segmentations, and feeding these segmentations to geometric and computational models for feature extraction. Working on the improved information flow with radiology involves aggregating the complete clinical data before and after the radiology examination, and assessing the value added by radiology across populations.

  
  
• Where do you work?

  University of Utah

  
  
• Expertise

  1. Biomedical Imaging
  2. Informatics
  3. Mathematics

  
  
• ORCiD

  (not set)

  
  
• Twitter

  (not set)

  
  
• Receive Email Updates

  Yes, send me emails