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Cost-Sensitive Machine Learning Classification for Mass Tuberculosis Verbal Screening
As such, the sensitivity of our identifier increased by 1. 26% while specificity increased by 13. 19% in absolute value compared to the traditional score-based method defined by our clinicians.
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