Bringing foundational models to the front lines of TB screening
Bringing foundational models to the front lines of TB screening
Over the past several years, our team across Google Research and Google for Health has worked to change that trajectory: moving from an AI-based tool that builds on our existing work in medical imaging to identify people with presumptive TB for follow-up testing to prospective clinical trials, regulatory clearance with local partners, and ultimately open foundation models like MedGemma that empower public health systems worldwide.
Selection record
Not admittedSum of both 116 < twice the threshold 120
- Source tier
- Official, first-hand; this tier's threshold is 60
- Pre-filter
- passed：Google Research用基础模型做结核筛查
A model scores each item twice, independently, against one written standard, out of 100. An item is admitted only when the two scores add up to twice the threshold. The threshold is set per source tier.
Source: Google Research · research.google