Article

Multimodal Gene Expression Deep Learning for Predicting Sentinel Lymph Node Macro-metastasis in Early Breast Cancer: Development and Validation in the SCAN-B Cohort

2026-04-02

Abstract excerpt

<title>Abstract</title> <p>Purpose: This study evaluates deep learning (DL) using gene expression (GEX) and preoperatively available clinical data (PreopClinic) to predict sentinel lymph node macro-metastasis (SLNM), and explores their potential for guiding axillary surgery de-escalation and supporting prognostic assessment. Experimental Design: We retrospectively included 6,836 clinically node-negative (cN0) T1-...

Topics

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

Identifiers and source

Literature Corpus work: f31cf8ab-0fa9-5cc1-ba3a-6c204e22d0ad
DOI: 10.21203/rs.3.rs-9281660/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Multimodal Gene Expression Deep Learning for Predicting Sentinel Lymph Node Macro-metastasis in Early Breast Cancer: Development and Validation in the SCAN-B CohortDOI 10.21203/rs.3.rs-9281660/v1Read

Integration of Gene Expression and Digital Histology to Predict Treatment-Specific Responses in Breast CancerSemantic proximity Read

Deep learning framework for comprehensive molecular and prognostic stratifications of triple-negative breast cancerSemantic proximity Read

Deep learning generates custom-made logistic regression models for explaining how breast cancer subtypes are classifiedSemantic proximity Read

Breast cancer histopathology image-based gene expression prediction using spatial transcriptomics data and deep learningSemantic proximity Read

Deep Learning approach for breast cancer discovery Via gene correlationSemantic proximity Read

Whole transcriptome analysis reveal MammaPrint and BluePrint-associated gene expression patterns with early lymph node metastasis in early-stage breast cancerSemantic proximity Read

Deep Learning on Histopathological Images to Predict Breast Cancer Recurrence Risk and Chemotherapy BenefitSemantic proximity Read

Deep learning from HE slides to predict the clinical benefit from adjuvant chemotherapy in hormone receptor-positive breast cancerSemantic proximity Read

AUTOSurv: Interpretable Deep Learning Framework for Cancer Survival Analysis Incorporating Clinical and Multi-omics DataSemantic proximity Read

Preoperative Prediction of Residual Cancer Burden After Neoadjuvant Chemotherapy in Breast Cancer: A Multimodal Machine Learning Approach and Implications for Clinical Decision SupportSemantic proximity Read

Predicting molecular subtypes of breast cancer using pathological images by deep convolutional neural network from public datasetSemantic proximity Read

A network-based deep learning model integrating subclonal architecture for therapy response prediction in cancerSemantic proximity Read