AI-Powered TB Detection

Faster Diagnosis. Better Outcomes.

Two advanced deep learning systems that analyze chest X-ray images to detect TB accurately and support clinical decision-making.

01

TBXNet — AI Model for TB Detection

Trained on thousands of annotated images. Detects subtle abnormalities with high precision and achieves nearly 99% accuracy, providing reliable decision support for clinicians.

99% AUC Accuracy Deep Learning
02

TBXNet++ — Advanced TB Detection with Visual Explanation

Hybrid model using classification and segmentation. Highlights diseased areas for better interpretability. Achieves about 95% accuracy with affected regions highlighted.

95% AUC Accuracy Visual Explainability DEMO

Global Recognition by Stop TB Partnership

TBXNet++ is globally recognized by Stop TB Platform for its innovation, accuracy, and impact in advancing the global fight against tuberculosis.

Stop TB Partnership UNOPS UN SDGs

Local Deployment — Greenstar Rawalpindi

TBXNet++ is actively deployed at Greenstar Rawalpindi to enhance TB screening and support better healthcare outcomes through faster AI-assisted diagnosis.

First Commercial Sale: DOPASI Foundation — Community-based TB screening