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The worst performing method was Decision Trees with an accuracy of 0.675, precision of 0.571, recall of 0.599, F1 score of 0.570 and ROC-AUC of 0.654 Conclusion: Using machine learning methods, we were able to predict the presence of fatty liver disease with high accuracy, precision, and recall
While these applications remain preclinical, they illustrate the broad regenerative potential of this peptide and explain why TB-500 features in so many multi-tissue recovery protocols
It doesnt impair function
Your body cant keep up
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