Sample pooling, in which equal volumes from multiple specimens are combined and tested together, can reduce per-sample costs and increase testing throughput while preserving clinical performance.

With hardware prices spiraling, AI vendors ramping up token costs, and models becoming drastically slimmer and more economical, running AI models locally isn’t just going to be a good idea whose time ...