Article

Cross-institutional HER2 assessment via a computer-aided system using federated learning and stain composition augmentation

2024-01-22

Abstract excerpt

The rapid advancement of precision medicine and personalized healthcare has heightened the demand for accurate diagnostic tests. These tests are crucial for administering novel treatments like targeted therapy. To ensure the widespread availability of accurate diagnostics with consistent standards, the integration of computer-aided systems has become essential. Specifically, computer-aided systems that assess biom...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 1a26e1e9-d84b-5c3c-ba3a-57b0c69ca168
DOI: 10.1101/2024.01.17.576160

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Cross-institutional HER2 assessment via a computer-aided system using federated learning and stain composition augmentationDOI 10.1101/2024.01.17.576160Read

Federated Learning-Driven Collaborative Diagnostic System for Metastatic Breast CancerSemantic proximity Read

Federated deep learning enables cancer subtyping by proteomicsSemantic proximity Read

Evaluating reproducibility of AI algorithms in digital pathology with DAPPERSemantic proximity Read

Comparison of the classification of HER2 from whole-slide images between pathologists and a deep learning modelSemantic proximity Read

A systematic analysis of deep learning in genomics and histopathology for precision oncology.Semantic proximity Read

Buyer Beware: confounding factors and biases abound when predicting omics-based biomarkers from histological imagesSemantic proximity Read

Deep learning in cancer genomics and histopathologySemantic proximity Read

Generalizing AI-driven Assessment of Immunohistochemistry across Immunostains and Cancer Types: A Universal Immunohistochemistry AnalyzerSemantic proximity Read

Deep learning framework for predicting EGFR mutation status from H&E whole slide images in lung adenocarcinoma.Semantic proximity Read

Machine learning enabled prediction of digital biomarkers from whole slide histopathology imagesSemantic proximity Read

FTAD-Net: Federated Transfer-Adversarial Learning for Robust Breast Cancer DetectionSemantic proximity Read

Classification and Interpretation of Histopathology Images: Leveraging Ensemble of EfficientNetV1 and EfficientNetV2 ModelsSemantic proximity Read