Inference on the validation set is xray -> pain score. It does not incorporate patient symptoms to make the prediction. In real life a surgeon incorporates the xray + patient symptoms/pain score.
Skipped a step: the model needs to be trained, which requires the patient symptoms as the target for weight updates. I think that you simply misread my original comment.
Perhaps I got lost but I am discussing your original statement of “using the patients' symptoms and objective data may actually outperform current medical standards” which relates to the model predictions/inference not training.
In this context we are talking about a pain predictor from an xray which is neat but not the point of KL grading.
The comparator, current medical standards you reference, would be a model outperforming surgeon assessment in conjunction with radiographic findings. Not the predictive value of KL grade.
carbocation|2 years ago
haldujai|2 years ago
In this context we are talking about a pain predictor from an xray which is neat but not the point of KL grading.
KL is a system to grade severity of osteoarthritis on radiographs (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4925407/) and not a threshold for surgery or predictor of symptoms.
The comparator, current medical standards you reference, would be a model outperforming surgeon assessment in conjunction with radiographic findings. Not the predictive value of KL grade.