2021 Fiscal Year Final Research Report
Development of a diagnostic learning system using decision tree
| Project/Area Number |
17K01134
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Multi-year Fund |
|---|
| Section | 一般 |
|---|
| Research Field |
Educational technology
|
|---|
| Research Institution | Kyushu University |
|---|
Principal Investigator |
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
吉浦 一紀 九州大学, 歯学研究院, 教授 (20210643)
徳安 達士 福岡工業大学, 情報工学部, 教授 (50435492)
|
|---|
| Project Period (FY) |
2017-04-01 – 2022-03-31
|
| Keywords | 診断学習 / 読影実習 |
|---|
| Outline of Final Research Achievements |
In previous medical diagnostic imaging training, students read the images given to them. In this study, we aim to create an environment in which students can learn the necessity of examinations by including a step for selecting an examination method in the diagnostic learning system.
We constructed a prototype of a diagnostic learning system in which students first select one necessary X-ray examination based on the chief complaint in the assignment sentence, read the image, and then select the next examination they consider necessary.
|
| Free Research Field |
歯科放射線
|
| Academic Significance and Societal Importance of the Research Achievements |
必要な検査を的確に選択する能力が向上することにより、将来的に実際の臨床の場で診断能力が向上することが期待できるのに加え、不要な検査を減らすことにより、被ばくをはじめとする検査のデメリットを軽減することが期待される。これらは良好な予後をはじめとする身体的なメリットだけでなく、検査軽減や的確な診断による治療期間短縮等による個人および社会的医療費の軽減も期待される。
|
