Unique ID issued by UMIN | UMIN000048005 |
---|---|
Receipt number | R000054722 |
Scientific Title | Development of diagnostic and therapeutic support tools for scoliosis using deep learning |
Date of disclosure of the study information | 2022/06/10 |
Last modified on | 2022/06/09 11:29:07 |
Development of diagnostic and therapeutic support tools for scoliosis using deep learning
Development of diagnostic and therapeutic support tools for scoliosis using deep learning
Development of diagnostic and therapeutic support tools for scoliosis using deep learning
Development of diagnostic and therapeutic support tools for scoliosis using deep learning
Japan | Asia(except Japan) | North America |
Australia | Europe |
Scoliosis
Orthopedics |
Others
NO
Image items related to the progression of scoliosis are evaluated using AI.
Efficacy
Exploratory
Explanatory
Not applicable
For X-ray images of patients with scoliosis, we will compare and examine which is more accurate, the progress prediction by AI or the progress prediction by a spine surgeon. We plan to use images from six months, one year, and two years to study the progress.
Images other than X-rays are also used as secondary outcomes. Patient groups are stratified and evaluated by degree of bone maturity.
Interventional
Single arm
Non-randomized
Open -no one is blinded
Self control
YES
NO
Institution is not considered as adjustment factor.
NO
No need to know
1
Prevention
Other |
X-ray of 6, 12, and 24 months in patients with scoliosis was evaluated.
10 | years-old | < |
80 | years-old | > |
Male and Female
idiopathic scoliosis
Exclude scoliosis from other disorders such as non-idiopathic, neurological, symptomatic, and congenital.
200
1st name | Shoji |
Middle name | |
Last name | Seki |
University of Toyama
Orthopaedic surgery
930-0194
Sugitani 2630
0764347353
seki@med.u-toyama.ac.jp
1st name | Shoji |
Middle name | |
Last name | Seki |
University of Toyama
Orthopaedic surgery
930-0194
Sugitani 2630
0764347353
seki@med.u-toyama.ac.jp
University of Toyama
Kakenhi
Japanese Governmental office
University of Toyama
Sugitani2630
0764347353
seki@med.u-toyama.ac.jp
NO
2022 | Year | 06 | Month | 10 | Day |
Unpublished
Open public recruiting
2019 | Year | 01 | Month | 01 | Day |
2019 | Year | 09 | Month | 25 | Day |
2019 | Year | 09 | Month | 25 | Day |
2025 | Year | 03 | Month | 31 | Day |
2022 | Year | 06 | Month | 09 | Day |
2022 | Year | 06 | Month | 09 | Day |
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000054722