‘Bayesian Framework’

Results for prediction of high-risk discharge GCS cases (a) Average ROC curves internal cross-validated sets (b) Average effect of each new feature that is added via the greedy feature selection method (c) ROC curve for the holdout dataset (d) Effect of each new feature that is added via the greedy feature selection method in the holdout dataset.

A Bayesian Framework for Early Risk Prediction in Traumatic Brain Injury

Feb. 15, 2016—Shikha Chaganti, Andrew J. Plassard, Laura Wilson, Miya A. Smith, Mayur B. Patel, Bennett A. Landman. A Bayesian Framework for Early Risk Prediction in Traumatic Brain Injury. In Proceedings of the SPIE Medical Imaging Conference. San Diego, California, February 2016. Full Text: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4845965/ Abstract Early detection of risk is critical in determining the course...