Machine learning algorithms for predicting future curve using first and second visit data in female adolescent idiopathic scoliosis patients
The ML-based model using items commonly evaluated at the first and second visits accurately predicted future Cobb angles in female patients with AIS.
Authors
- Tsutomu Akazawa (ORCID: https://orcid.org/0000-0003-2348-0994)
- Seiji Ohtori (ORCID: https://orcid.org/0000-0001-5738-6184)
- Masahiro Inoue (ORCID: https://orcid.org/0000-0002-9518-9189)
- Shohei Minami (ORCID: https://orcid.org/0000-0002-3999-348X)
- Noritaka Suzuki (ORCID: https://orcid.org/0000-0002-5009-1786)
- Soichiro Tokeshi
- Sumihisa Orita (ORCID: https://orcid.org/0000-0003-2676-5469)
- Susumu Tashiro (ORCID: https://orcid.org/0009-0006-8126-1289)
- Noriyasu Toshi (ORCID: https://orcid.org/0000-0003-3424-7469)
- Kazuhide Inage (ORCID: https://orcid.org/0000-0003-0540-4613)
- Satoshi Maki (ORCID: https://orcid.org/0000-0002-6809-3771)
- Kohei Okuyama
- Yosuke Ogata (ORCID: https://orcid.org/0000-0001-8898-534X)
- Yasushi Iijima (ORCID: https://orcid.org/0000-0003-0141-446X)
- Toshiaki Kotani (ORCID: https://orcid.org/0000-0002-0659-2970)
- Takahito Arai
- Yasuhiro Shiga (ORCID: https://orcid.org/0000-0003-4887-0008)
- Yawara Eguchi (ORCID: https://orcid.org/0000-0003-2247-5376)
- Shuhei Ohyama (ORCID: https://orcid.org/0000-0002-2947-4870)
- Tsuyoshi Sakuma
Institutions
- Chiba University (JP)
- St. Marianna University School of Medicine (JP)
- Seirei Sakura Citizen Hospital (JP)
Publication Details
- Journal
- European Spine Journal
- Published
- 2025-02-04
- DOI
- https://doi.org/10.1007/s00586-025-08680-9
- Citations
- 2
- Primary Topic
- Scoliosis diagnosis and treatment
- Type
- article
- Field-Weighted Citation Impact
- 4.01