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Fig. 4 | BMC Medicine

Fig. 4

From: Machine learning approaches classify clinical malaria outcomes based on haematological parameters

Fig. 4

Non-symmetrical predictive values of clinical diagnosis using median split (high vs low levels) of each haematological parameter. A ‘median split’ was used to divide each quantitative parameter into categorical variables by the median value (calculated as a mean of nMI and UM or SM median value shown in Table 2). The predictive values are calculated from contingency tables (Additional file 2: Table S3). a The percentage predictive value in predicting nMI from low levels. b Percentage predictive value in predicting SM or UM using the low levels. c Percentage predictive value in predicting nMI using high levels. d Predictive values of UM or SM using high levels

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