Table 4.

Limitations of and improvement measures for AI and ML in spinal care.

Limitations	Improvement Measures
Lack of high-quality, diverse data	Ensure data collection with proper annotation and labeling Expand data sources and collaborations Implement data augmentation techniques to increase dataset diversity
Potential bias and fairness issues	Develop bias detection and mitigation techniques Implement fairness-aware algorithms Conduct rigorous evaluation of models for bias and fairness
Interpretability and explainability	Develop transparent and interpretable AI and ML models Create model-agnostic interpretability techniques Provide explanations for model predictions and decisions
Generalizability and transferability	Collect data from diverse populations and settings Explore transfer-learning and domain-adaptation techniques Conduct external validation studies across different healthcare settings