Machine learning models from computed tomography to diagnose thymic epithelial tumors requiring combined resection
The machine learning model based on preoperative CT images was able to diagnose TETs requiring combined resection with high accuracy. The DCA demonstrated a wide range of model validity and may aid in surgical approach selection.
Authors
- Takamasa Ito (ORCID: https://orcid.org/0000-0003-4220-3861)
- Hiroki Matsumoto (ORCID: https://orcid.org/0000-0003-4044-0281)
- Tomohiko Iida
- Hidemi Suzuki (ORCID: https://orcid.org/0000-0002-8983-433X)
- Yuki Onozato (ORCID: https://orcid.org/0000-0002-6298-707X)
- Takekazu Iwata (ORCID: https://orcid.org/0000-0003-4411-6825)
- Yuichi Sakairi (ORCID: https://orcid.org/0000-0003-0222-0253)
- Toshihiko Iizasa
- Yukiko Matsui (ORCID: https://orcid.org/0000-0003-1515-7468)
- Takayoshi Yamamoto (ORCID: https://orcid.org/0000-0002-0746-2924)
- Ichiro Yoshino (ORCID: https://orcid.org/0009-0003-4007-9606)
- Kazuhisa Tanaka
Institutions
- Chiba Cancer Center (JP)
Publication Details
- Journal
- Journal of Thoracic Disease
- Published
- 2024-08-01
- DOI
- https://doi.org/10.21037/jtd-23-1840
- Citations
- 1
- Primary Topic
- Myasthenia Gravis and Thymoma
- Type
- article
- Field-Weighted Citation Impact
- 0.37
Funders
- Pfizer
- Taiho Pharmaceutical
- Intuitive Surgical
- Daiichi-Sankyo
- Shionogi
- Chugai Pharmaceutical