Risk analysis for astronaut selection during space flight cardio vascular problems — Classification using random forest algorithm

Arrhythmia is the major cause of cardiovascular events during space flight. Even though a number of physical tests are conducted to diagnose the disease, in most of the cases the issue remains undetected because of the hidden problems which cannot be pinpointed with regular physical tests. A computation system which can assist in decision making for astronaut selection for space flight is proposed using machine learning approach. The present paper attempts to evaluate ‘random forest’ algorithm for classification. The system is implemented in MATLAB. It makes use of ‘random forest’ as the classification algorithm. It is found that an average accuracy of 74.5% is attainable. It is also observed that the accuracy does not improve beyond a particular threshold number of decision trees in ‘random forest’.