Machine-learning-based models for the optimization of post-cervical spinal laminoplasty outpatient follow-up schedules
This study was registered as a clinical trial (Clinical Trial No. NCT02487901), and the study protocol was approved by the Seoul National University Hospital Institutional Review Board (IRB No. 1505-037-670).
Authors
- Seoi Jeong
- Hyoun‐Joong Kong (ORCID: https://orcid.org/0000-0001-5456-4862)
- Chi Heon Kim (ORCID: https://orcid.org/0000-0003-0497-1130)
- John M. Rhee (ORCID: https://orcid.org/0000-0002-6172-3590)
- Chang-Hyun Lee (ORCID: https://orcid.org/0000-0003-0134-2101)
- Junhoe Kim (ORCID: https://orcid.org/0000-0001-5866-9952)
- Chun Kee Chung (ORCID: https://orcid.org/0000-0003-3485-2327)
- Joongku Lee (ORCID: https://orcid.org/0000-0001-6250-3138)
- Taeshin Kim (ORCID: https://orcid.org/0000-0002-7078-4387)
- Yechan Seo
Institutions
- Seoul National University (KR)
- Emory University (US)
- New Generation University College (ET)
- Seoul National University Hospital (KR)
- Seoil University (KR)
- National University College (PR)
- Newcastle University (GB)
Publication Details
- Journal
- BMC Medical Informatics and Decision Making
- Published
- 2024-09-30
- DOI
- https://doi.org/10.1186/s12911-024-02693-y
- Citations
- 2
- Primary Topic
- Medical Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.37
Funders
- Seoul National University
- Doosan Heavy Industries and Construction
- Korea Health Industry Development Institute
- Seoul National University Hospital
- Ministry of Education, India
- Doosan Yonkang Foundation