Published 27 Sep 2020

How Deep Learning Is Used For Tuberculosis Detection In City Of Nagpur

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The global fight against Tuberculosis (TB), one of the world's most deadly infectious diseases, has found a strong ally in Artificial Intelligence (AI).
In India, where the disease affects over 27 lakh lives yearly, Qure.ai, a leading healthcare-focused AI firm, has stepped up to tackle this crisis in collaboration with PATH, a non-profit organization.
The initiative's primary target was the Maharashtra city of Nagpur, with 35% of its population suffering from TB. The region largely relies on informal healthcare providers who, while affordable and accessible, lack the necessary tools for early TB detection.
Enter qXR, Qure.ai's AI-powered chest X-ray interpretation platform. This revolutionary tool can accurately detect 29 different, clinically relevant lung markers, playing a vital role in identifying classic and atypical TB forms. It processes X-rays within minutes, swiftly identifying potential cases and alerting healthcare providers to expedite treatment procedures.
The tool's deep learning algorithms have been trained on a dataset of 3.6 million chest X-rays gathered from around 250 sites globally over four years. This AI-driven system can analyze multiple scans from the same patient sequentially, providing a progress report to track changes in lesions over time.
Dr. Shibu Vijayan, Global TB Technical Director at PATH, reported a 20% increase in the notification of TB cases since the implementation of qXR.
With TB diagnosis drastically expedited, this system promises a promising future for rural healthcare providers seeking to tackle the rampant disease.

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