Galina Khramtsova

May 29, 2023 | nature.com | Andrew Srisuwananukorn |Jefree J. Schulte |Galina Khramtsova |Robert Grossman

Dataset descriptionThe Lung cGAN was trained on 941 whole-slide images (WSI) from The Cancer Genome Atlas (TCGA), including 467 slides from the lung adenocarcinoma project (TCGA-LUAD) and 474 slides from the lung squamous cell carcinoma project (TCGA-LUSC) (https://portal.gdc.cancer.gov/).

Apr 14, 2023 | nature.com | Frederick Howard |James M. Dolezal |Andrew Srisuwananukorn |Rita Nanda |Charles M. Perou |Olufunmilayo I. Olopade | +2 more

AbstractGene expression-based recurrence assays are strongly recommended to guide the use of chemotherapy in hormone receptor-positive, HER2-negative breast cancer, but such testing is expensive, can contribute to delays in care, and may not be available in low-resource settings. Here, we describe the training and independent validation of a deep learning model that predicts recurrence assay result and risk of recurrence using both digital histology and clinical risk factors.