Cancer Dataset

Cancer datasets are collections of patient data, including genomic information, pathology images (whole slide images, H&E stained slides), and clinical records, used to develop and evaluate machine learning models for cancer diagnosis, prognosis, and treatment selection. Current research focuses on developing robust and generalizable models, often employing deep learning architectures like convolutional neural networks (CNNs), graph neural networks (GNNs), and vision-language models (VLMs), to analyze high-dimensional data and predict various biomarkers, including gene expression, mutation burden, and treatment response. These advancements hold significant promise for improving the accuracy and efficiency of cancer diagnostics, guiding personalized treatment strategies, and accelerating clinical trial recruitment.