| Project/Area Number |
17K17845
|
|---|
| Research Category |
Grant-in-Aid for Young Scientists (B)
|
| Allocation Type | Multi-year Fund |
|---|
| Research Field |
Lifelong developmental nursing
Clinical nursing
|
|---|
| Research Institution | Osaka University |
|---|
Principal Investigator |
Kikuchi Ryota 大阪大学, 大学院医学系研究科, 講師 (40794037)
|
|---|
| Project Period (FY) |
2017-04-01 – 2023-03-31
|
| Project Status |
Completed (Fiscal Year 2022)
|
| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2019: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2018: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2017: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
|
|---|
| Keywords | 臓器移植 / 小児 / Quality of life / Patient-reported outcome / 長期フォローアップ / Artificial intelligence / Quality of Life / 患者報告型アウトカム / HRQOL / 看護 / 人工知能 / 成人 / 長期成績 / 横断的研究 / 小児看護学 / 成人看護学 / QOL / 長期支援 |
|---|
| Outline of Final Research Achievements |
Since artificial intelligence (AI) is an indispensable technology in establishing a database for long-term follow-up of patients who underwent organ transplantation in childhood, we conducted a systematic review of the utility of AI in healthcare, especially in the field of nursing. The review revealed that machine learning was used, and that AI had utility in predicting depression based on patients' self-reports. The establishment of a long-term follow-up system based on AI, which is the theme of this study, will enable prompt and accurate support for organ transplant patients.
|
| Academic Significance and Societal Importance of the Research Achievements |
小児期に臓器移植を行った患者の長期的なアウトカムは着目されつつあるも、長期フォローアップについては課題となっている。本研究にて、長期フォローアップに向けたデータベースの確立に際してAIが基幹となりうることが確認されたことは患者の支援をより充実させるために有用な知見であり、臓器移植患者だけでなく他の疾患・治療を行う患者への応用可能性も示唆される。
|
