| Unique ID issued by UMIN | UMIN000043211 |
|---|---|
| Receipt number | R000049318 |
| Scientific Title | Development of artificial intelligence in ophthalmology |
| Date of disclosure of the study information | 2021/02/01 |
| Last modified on | 2022/02/02 11:48:15 |
Development of artificial intelligence in ophthalmology
Development of artificial intelligence in ophthalmology
Development of artificial intelligence in ophthalmology
Development of artificial intelligence in ophthalmology
| Japan |
Cataract, dry eye disease, allergic conjunctivitis, glaucoma, corneal disease, etc
| Ophthalmology | Adult | Child |
Others
NO
Development of artificial intelligence using ophthalmology data
Efficacy
Performance of artificial intelligence in the diagnosis or/and evaluation of ophthalmologic data.
Observational
| 16 | years-old | <= |
| 100 | years-old | > |
Male and Female
All patients
no opt-in cases
905
| 1st name | Eisuke |
| Middle name | |
| Last name | Shimizu |
Keio University School of Medicine
Department of Ophthalmology
160-8582
35 Shinanomachi, Shinjuku-ku
0333531211
ophthalmolog1st.acek39@keio.jp
| 1st name | Eisuke |
| Middle name | |
| Last name | Shimizu |
Keio University School of Medicine
Department of Ophthalmology
160-8582
35 Shinanomachi, Shinjuku-ku
0333531211
ophthalmolog1st.acek39@keio.jp
Keio University School
AMED
Japanese Governmental office
Keio University School of Medicine
35 Shinanomachi, Shinjuku-ku
0333531211
ophthalmolog1st.acek39@keio.jp
NO
| 2021 | Year | 02 | Month | 01 | Day |
Unpublished
Enrolling by invitation
| 2021 | Year | 02 | Month | 01 | Day |
| 2021 | Year | 02 | Month | 01 | Day |
| 2021 | Year | 02 | Month | 01 | Day |
| 2023 | Year | 09 | Month | 30 | Day |
none
| 2021 | Year | 02 | Month | 01 | Day |
| 2022 | Year | 02 | Month | 02 | Day |
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000049318