Google Research deploys open foundation models like MedGemma for global TB screening
Google Research and Google for Health are deploying open foundation models, such as MedGemma, to democratize tuberculosis (TB) screening globally, addressing the scarcity of radiologists in high-burden settings. Initial work demonstrated deep learning algorithms could detect active pulmonary TB on chest radiographs with accuracy matching expert radiologists (2019). The model was ranked among top global TB screening algorithms by the Stop TB Partnership (2021), and a prospective multi-site validation in NEJM AI (2024) confirmed high sensitivity across diverse populations. In partnership with Nexus AI, the tool has received regulatory clearance (CE MDR Class IIb) and has been deployed in 40 medical institutions across countries like South Africa and Sierra Leone, screening over 25,000 chest X-rays.
This work demonstrates the full pipeline from AI algorithm development to real-world clinical deployment, using open models and local deployment to overcome data privacy and computational resource challenges in low-resource settings.
Source: Google Research · research.google