As single-cell datasets grow from thousands to hundreds of thousands of cells, accurate cell annotation is becoming a major bottleneck in biomedical research.
In this episode of To Immunity and Beyond, bioinformatician Rufus Daw discusses CellTypeAI, a new locally deployable AI framework that uses large language models to automate cell-type identification from single-cell RNA sequencing data.
We explore how privacy-preserving AI tools, retrieval-augmented generation, and ensemble prompting can match or exceed conventional annotation approaches while keeping sensitive research data entirely in-house, and what this means for the future of AI-assisted immunology and systems biology.