Sagittal MRI from 120 confirmed patients is split at patient level to train models distinguishing spinal tuberculosis, pyogenic infection and metastasis. The task is clinically relevant, but small retrospective data and manual lesion annotation require external prospective validation.
Key findings
- Sagittal MRI from 120 confirmed patients is split at patient level to train models distinguishing spinal tuberculosis, pyogenic infection and metastasis. The task is clinically relevant, but small retrospective data and manual lesion annotation require external prospective validation.
Why this matters globally
This work adds internationally comparable evidence in Health sciences and defines questions for replication in other populations or systems. Its global value lies in the evidence and transferable reasoning, not in a single impact score.
Thai researcher contribution
Thailand-linked authors and Chiang Mai University, University of Phayao contribute to the research network behind this work. Thai participation is identified from bibliographic affiliations and should be checked against the author list and source article.
Limitations to consider
Performance can fall under dataset shift; external validation, leakage checks, calibration and post-deployment monitoring are needed.