  Low back pain (LBP) and sciatica may require surgical therapy when they are
symptomatic of severe pain. However, there is no effective measures to evaluate
the surgical outcomes in advance. This work combined elements of Eastern
medicine and machine learning, and developed a preoperative assessment tool to
predict the prognosis of lumbar spinal surgery in LBP and sciatica patients.
Standard operative assessments, traditional Chinese medicine body constitution
assessments, planned surgical approach, and vowel pronunciation recordings were
collected and stored in different modalities. Our work provides insights into
leveraging modality combinations, multimodals, and fusion strategies. The
interpretability of models and correlations between modalities were also
inspected. Based on the recruited 105 patients, we found that combining
standard operative assessments, body constitution assessments, and planned
surgical approach achieved the best performance in 0.81 accuracy. Our approach
is effective and can be widely applied in general practice due to simplicity
and effective.
