Mortality prediction of rats in acute hemorrhagic shock using machine learning techniques

A New Severity Predicting Index for Hemorrhagic Shock Using Lactate Concentration and Peripheral Perfusion in a Rat Model

(2012) Joon Yul Choi et al.   SHOCK

Optimized application of penalized regression methods to diverse genomic data

(2011) Levi Waldron et al.   BIOINFORMATICS

Unexpected 100% Survival Following 60% Blood Loss Using Small-Volume 7.5% NaCl With Adenocaine and Mg2+ in the Rat Model of Extreme Hemorrhagic Shock

(2011) Hayley L. Letson et al.   SHOCK

Novel solutions for an old disease: Diagnosis of acute appendicitis with random forest, support vector machines, and artificial neural networks

(2010) Chung-Ho Hsieh et al.   SURGERY

A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification

(2008) Alexander Statnikov et al.   BMC BIOINFORMATICS

Mass Casualty Triage: An Evaluation of the Data and Development of a Proposed National Guideline

(2008) E. Brooke Lerner et al.   Disaster Medicine and Public Health Preparedness