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Metabolite-based machine learning models reveal biomarkers of urinary, gait, and cognitive outcomes Following identification of metabolites associated with clinical response, we applied machine-learning approaches to model shunt outcomes using Partial Least SquaresDiscriminant Analysis (PLS-DA) and Support Vector Machine (SVM) classifiers

We have summarized the resistance of GH and IGF1 signaling pathways to radiotherapy, which is not conducive to treatment, but a large number of studies have shown that they have recovery effect on the damage of adjacent tissues post-radiotherapy

The two routes use fundamentally different dosing logic, and mixing them produces incorrect protocols

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