| Unique ID issued by UMIN | UMIN000047720 |
|---|---|
| Receipt number | R000054395 |
| Scientific Title | Development of AI to diagnose the corneal infection |
| Date of disclosure of the study information | 2022/05/11 |
| Last modified on | 2022/05/11 16:16:31 |
Development of AI to diagnose the corneal infection
Development of AI to diagnose the corneal infection
Development of AI to diagnose the corneal infection
Development of AI to diagnose the corneal infection
| Japan | Asia(except Japan) |
Corneal infection
| Ophthalmology |
Others
NO
Development of AI to diagnose the corneal infection
Others
NA
Whether AI shows accuracy to suggest causative organism >60%
Others,meta-analysis etc
| 20 | years-old | <= |
| Not applicable |
Male and Female
Corneal infection
The causative organism was not detected.
Infection focus covers the whole area of the cornea.
Insufficient quality of anterior segment images.
Patients who are not willing to be involved in the study.
200
| 1st name | Naoki |
| Middle name | |
| Last name | Okumura |
Doshisha University
Department of Biomedical Engineering
610-0394
1-3 tatara MIyakodani, Kyotanabe, Japan
0774656508
nokumura@mail.doshisha.ac.jp
| 1st name | Naoki |
| Middle name | |
| Last name | Okumura |
Doshisha University
Department of Biomedical Engineering
610-0394
1-3 tatara MIyakodani, Kyotanabe, Japan
0774656508
nokumura@mail.doshisha.ac.jp
Doshisha University
Ministry of Education, Culture, Sports, Science and Technology, MEXT
Japanese Governmental office
IRB
1-3 tatara MIyakodani, Kyotanabe, Japan
075-251-3158
ji-rinri@mail.doshisha.ac.jp
NO
| 2022 | Year | 05 | Month | 11 | Day |
Unpublished
Enrolling by invitation
| 2022 | Year | 02 | Month | 21 | Day |
| 2022 | Year | 02 | Month | 21 | Day |
| 2022 | Year | 02 | Month | 21 | Day |
| 2024 | Year | 03 | Month | 31 | Day |
NA
| 2022 | Year | 05 | Month | 11 | Day |
| 2022 | Year | 05 | Month | 11 | Day |
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000054395