23 Sep Top predictive features selected for the four classification algorithms
Top predictive features selected for the four classification algorithms (A) Top three predictive features identified using the recursive feature elimination method for the four classification algorithms across the 100 runs used to select the most discriminative features and train the corresponding candidate prediction models; the values in parentheses indicate the number of times the feature was selected as top ranked in the development dataset. Minimum oxygen saturation (B) and age (C) features, which were selected as top predictive features for all the four algorithms, are presented as violin plots showing the distributions of the values in the development dataset. In panels B and C, the black boxplots in the middle show the distribution of the values on the y axis, with the white dot indicating the median value; the width of the grey shape at a given value on the y axis indicates the probability of occurrence of that value in the population shown. The plots in panel B show that the median value (79%) of minimum oxygen saturation for the deceased group was significantly lower