Article

Direct prediction of Homologous Recombination Deficiency from routine histology in ten different tumor types with attention-based Multiple Instance Learning: a development and validation study

2023-03-10

Abstract excerpt

<h4>Background</h4> Homologous Recombination Deficiency (HRD) is a pan-cancer predictive biomarker that identifies patients who benefit from therapy with PARP inhibitors (PARPi). However, testing for HRD is highly complex. Here, we investigated whether Deep Learning can predict HRD status solely based on routine Hematoxylin & Eosin (H&E) histology images in ten cancer types. <h4>Methods</h4> We developed a fully a...

Topics

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

Identifiers and source

Literature Corpus work: c549e8f8-7a82-5f04-8b87-b8781beeceb8
DOI: 10.1101/2023.03.08.23286975

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Direct prediction of Homologous Recombination Deficiency from routine histology in ten different tumor types with attention-based Multiple Instance Learning: a development and validation studyDOI 10.1101/2023.03.08.23286975Read

AI-Enabled Prediction of Homologous Recombination Deficiency from Histopathology ImagesSemantic proximity Read

HRDPath: An Explainable Multi-Model Deep Learning Architecture for Predicting Homologous Recombination Deficiency from Histopathology ImagesSemantic proximity Read

Deep learning predicts HRD and platinum response from histology slides in breast and ovarian cancerSemantic proximity Read

Validation of Genomic and Transcriptomic Models of Homologous Recombination Deficiency in a Real-World Pan-Cancer CohortSemantic proximity Read

Multi-Omics Deep-Learning Prediction of Homologous Recombination Deficiency-Like Phenotype Improved Risk Stratification and Guided Therapeutic Decisions in Gynecological CancersSemantic proximity Read

Homologous recombination deficiency prediction from whole slide images using label refinement and foundation-model benchmarking in ovarian cancerSemantic proximity Read

Validation of genomic and transcriptomic models of homologous recombination deficiency in a real-world pan-cancer cohortSemantic proximity Read

DirectHRD enables sensitive scar-based classification of homologous recombination deficiencySemantic proximity Read

GIInger predicts homologous recombination deficiency and patient response to PARPi treatment from shallow genomic profilesSemantic proximity Read

Development of model for identifying homologous recombination deficiency (HRD) status of ovarian cancer with deep learning on whole slide imagesSemantic proximity Read

IHGAMP: Pan-cancer HRD prediction from routine H&E whole-slide images using foundation modelsSemantic proximity Read

Regulators of homologous recombination deficiency identified by machine learning using somatic multi-omics data.Semantic proximity Read