15 citations · 22 across the 3 of their papers we have counts for
3 papers
STEP: A Modular Silent Trial Engine for Operational Evaluation of Digital Pathology AI in Routine Workflow
Gabriele Campanella, Matthew Croken, Olga Lukatskaya +4
Prospective silent trials provide an important bridge between retrospective validation of artificial intelligence (AI) models and their use in clinical care by evaluating model per…
A Clinical Benchmark of Public Self-Supervised Pathology Foundation Models
Gabriele Campanella, Shengjia Chen, Ruchika Verma +10
The use of self-supervised learning (SSL) to train pathology foundation models has increased substantially in the past few years. Notably, several models trained on large quantitie…
Computational Pathology at Health System Scale -- Self-Supervised Foundation Models from Three Billion Images
Gabriele Campanella, Ricky Kwan, Eugene Fluder +10
Recent breakthroughs in self-supervised learning have enabled the use of large unlabeled datasets to train visual foundation models that can generalize to a variety of downstream t…