Albumentations is shared image-augmentation infrastructure for life-sciences AI. It shows up in radiology, histopathology, microscopy, endoscopy, ophthalmology, infectious-disease imaging, neuroscience imaging, and cell-analysis workflows. This post is the receipts: how many life-sciences papers cite it, which OSS library declares it as a direct dependency, which named organizations import it in public repositories, and where it appears in public Hugging Face model and dataset cards. All numbers below come from an internal evidence pipeline over public sources: citation metadata, GitHub Code Search, the Hugging Face Hub , and root-level packaging files ( requirements.txt , pyproject.toml , etc.) in each OSS repo. The derived CSVs used for this audit are not published with the blog post, so treat the tables as an evidence brief rather than a fully self-contained replication package. The org-scoped GitHub query is org:<name> "import albumentations" .…