Radiological Physics and Technology

, Volume 4, Issue 1, pp 29-36

First online:

Quantitative evaluation of expression difference in report assignments between nursing and radiologic technology departments

  • Naoki NishimotoAffiliated withDepartment of Healthcare Systems Research, Graduate School of Medicine, Hokkaido UniversityDepartment of Clinical Trial Management, Hokkaido Organization for Translational Research, Graduate School of Medicine, Hokkaido University Email author 
  • , Yuki YokookaAffiliated withDepartment of Radiology, Clark HospitalGraduate School of Health Sciences, Hokkaido University
  • , Ayako YagaharaAffiliated withGraduate School of Health Sciences, Hokkaido University
  • , Masahito UesugiAffiliated withDepartment of Medical Management and Informatics, Hokkaido Information University
  • , Katsuhiko OgasawaraAffiliated withFaculty of Health Sciences, Hokkaido University


Our purpose in this study was to investigate the expression differences in report assignments between students in nursing and radiologic technology departments. We have known that faculties could identify differences, such as word usage, through grading their students’ assignments. However, there are no reports in the literature dealing with expression differences in vocabulary usage in medical informatics education based on statistical techniques or other quantitative measures. The report assignment asked for students’ opinions in the event that they found a rare case of a disease in a hospital after they graduated from professional school. We processed student report data automatically, and we applied the space vector model and TF/IDF (term frequency/inverse document frequency) scoring to 129 report assignments. The similarity-score distributions among the assignments for these two departments were close to normal. We focused on the sets of terms that occurred exclusively in either department. For terms such as “radiation therapy” or “communication skills” that occurred in the radiologic technology department, the TF/IDF score was 8.01. The same score was obtained for terms such as “privacy guidelines” or “consent of patients” that occurred in the nursing department. These results will help faculties to provide a better education based on identified expression differences from students’ background knowledge.


Education Medical informatics TF/IDF Space vector model Natural language processing