7 citations · 7 across the 2 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…
Benchmarking Embedding Aggregation Methods in Computational Pathology: A Clinical Data Perspective
Shengjia Chen, Gabriele Campanella, Abdulkadir Elmas +8
Recent advances in artificial intelligence (AI), in particular self-supervised learning of foundation models (FMs), are revolutionizing medical imaging and computational pathology…