Mar 30, 2022 · We evaluate the performance of federated learning (FL) in developing deep learning models for analysis of digitized tissue sections.
We evaluate the performance of federated learning (FL) in developing deep learning models for analysis of digitized tissue sections. A classification ...
This paper presents a Federated Learning (FL) approach to a Tumor-Infiltrating Lymphocytes (TIL) application in a cloud computing en- vironment. The results ...
In this work, we are interested in analyzing the performance of a Tumor-Infiltrating Lymphocytes Classification problem when solved by a federated learning ...
Dec 5, 2022 · Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare ...
This paper presents a Federated Learning (FL) approach to a cloud Tumor-Infiltrating Lymphocytes (TIL) application. The results show that the FL approach ...
Integrated approach of federated learning with transfer ... - NCBI
www.ncbi.nlm.nih.gov › PMC11097560
May 15, 2024 · Our research builds upon and extends these developments by proposing a federated learning-based deep learning model, utilizing a modified VGG16 ...
Missing: Lymphocytes. | Show results with:Lymphocytes.
arXiv:2204.10836 (2022). 3U.Baid, et al. "Federated Learning for the Classification of Tumor Infiltrating Lymphocytes." arXiv preprint. arXiv:2203.16622 ...
Sep 2, 2024 · Our platform orchestrates federated training for joint tumor classification and segmentation across 19 international sites. FL-PedBrain ...
Missing: Infiltrating Lymphocytes.
Other recently published studies that have relied on WSI models (77, 78) include one that used a federated learning model to predict NAC response in TNBC, and ...