{"slug":"benchmark","tag":"benchmark","variants":["benchmark"],"description":"No description yet","count":2,"kinds":{"collection":1,"technology":1},"related":[{"slug":"data","tag":"data","shared":1},{"slug":"virtual-cell","tag":"virtual-cell","shared":1}],"records":[{"id":"pathology-benchmarks","kind":"collection","name":"Pathology AI benchmarks (CAMELYON, PANDA, TCGA slide tasks)","route":"/collections/pathology-benchmarks/","tldr":"Pathology AI benchmarks are the open challenge datasets on which every pathology model is scored: CAMELYON16 and 17 for lymph node metastasis detection, PANDA for prostate grading with 11,000 biopsies, and TCGA slide-level tasks used to compare foundation models. Licences are mostly CC BY-NC-SA or set per challenge."},{"id":"gears","kind":"technology","name":"GEARS and perturbation prediction benchmarks","route":"/technologies/gears/","status":"emerging","tldr":"GEARS is a graph model predicting the effect of gene knockouts; the perturbation benchmarks around it showed how hard the problem is."}]}