Researchers introduced a convolutional neural network (CNN) approach intended to quantify antibiotic resistance in Mycobacterium tuberculosis and predict patient treatment responses. The report describes the method as capable of achieving diagnostic-grade accuracy and extending beyond classification into treatment prediction. If validated at scale, the model could shorten time-to-decision for resistance-guided therapy and support more responsive regimen selection for multidrug-resistance management.