19 datasets found

A dataset containing samples from several patients with lung cancer.

The dataset contains data related to the study of lung cancer. It is a large-scale synthetic SCM designed to simulate data related to the study of lung cancer.

The dataset used for testing the proposed deep learning pipeline for tumor detection, histological subtyping, and EGFR mutation prediction from whole slide images (WSIs) of lung...

The dataset used for training and testing the proposed deep learning pipeline for tumor detection, histological subtyping, and EGFR mutation prediction from whole slide images...

The dataset contains clinical text from Spanish clinical narratives for lung cancer domain.

The CLARO dataset consists of clinical information of 297 patients suffering from non-small cell lung cancer.

The Danish Lung Cancer Screening Trial dataset consists of 32 inspiratory low-dose chest CT scans from participants with a history of smoking.

The dataset is used for multi-omics analysis in lung cancer.

A large-scale lung nodule dataset with pathology- or follow-up-confirmed benign/malignant labels for low-dose and noncontrast CTs.

The dataset used in this study for early lung cancer screening support combining low-dose CT-based radiomics and metabolomics.

The lung cancer dataset collects samples from 27 patients, and measures 31 proteins per cell.

The WSSS4LUAD challenge dataset contains 10,091 patch-level annotations and over 130 million labeled pixels from 87 WSIs of lung adenocarcinoma.

The Norwegian Lung Cancer Biobank (NLCB) cohort and the Bergen cohort were used to create the proposed model. The NLCB cohort includes histopathological, cytological, biomarker,...

The Norwegian Lung Cancer Biobank (NLCB) cohort and the Bergen cohort were used to create the proposed model. The NLCB cohort includes histopathological, cytological, biomarker,...

The TCGA-NSCLC dataset includes two sub-types of lung cancer, Lung Adenocarcinoma (LUAD) and Lung Squamous Cell Carcinoma (LUSC).

WSSS4LUAD dataset, comprising tissue samples from lung and colon adenocarcinomas, divided into two distinct subsets: LC-lung and LC-colon.

The dataset used in this study was obtained from two hospitals, including a total of 483 pulmonary nodules collected from 426 patients.

The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) dataset is used for training and testing a ResNet-50 model to classify CT scans of lungs...

The Lung Cancer part of the dataset LC25000 has 25,000 color images in 5 classes. Each class contains 5,000 images of the histologic categories: colon adenocarcinoma, benign...