Biography

Saniya Pawar serves as Vice President, Operations at Qure.ai, where she leads health economics and outcomes research to drive the adoption of AI in healthcare. She has over 10 years of experience in implementation research. Saniya graduated from IIT Bombay in 2015 with a B.Tech in Metallurgical Engineering and a minor in Humanities and Social Sciences
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Expertise

TB Diagnostics
Public Health

Key Impacts

Chest X-ray artificial intelligence for detection of paediatric pulmonary TB: A multi-site retrospective diagnostic accuracy study from rural and peri-urban India

AI had good accuracy in detecting confirmed and unconfirmed paediatric PTB using CXRs. CXRs from children with previous history of TB were more prone to have inaccurate AI results. Accuracy was not affected by age, gender and contact history.

Source: Conference 2024
Acceptability and feasibility of an AI-powered care co-ordination tool in TB management in Patient Provide Supporter Agency (PPSA) service implementation model in India: Qualitative insights

AI-enabled tools strengthen TB surveillance and patient management by optimizing existing workflows, improving real-time care coordination, and operational efficiency across PPSA agencies and the NTEP, without requiring additional infrastructure investments.

Source: Conference 2024
Intensified TB case finding in private hospitals in India: Transforming the incidental screening pathway with computer-aided detection

CAD was integrated within the PPSA initiative to facilitate intensified TB case finding in private hospitals using Chest X-rays. A significant increase in TB notifications was observed from these facilities at the end of the intervention period, thus showing promise for scale up of this approach at national level to improve yield and patient outcomes.

Source: Conference 2024