Bringing foundational models to the front lines of TB screening

Google Research and Google for Health describe their path from a 2019 Radiology benchmark showing deep learning could match radiologists in detecting active pulmonary TB to prospective multi-site validation, CE MDR Class IIb certification via Nexus AI, and deployment in about 40 facilities across six countries, where over 90 clinicians have evaluated more than 25,000 chest radiographs. They also detail offline AI screening four kilometers underground at South Africa's Mponeng Gold Mine and open models (HAI-DEF, MedSigLIP, MedGemma, HeAR), including Indonesia's Ministry of Health fine-tuning MedGemma and MedSigLIP on domestic chest radiographs for a national TB program.