A large histological images dataset of gastric cancer with tumour microenvironment annotation for AI.

Gastric cancer (GC) is the third leading cause of cancer death worldwide. Its clinical course varies considerably due to the highly heterogeneous tumour microenvironment (TME). Decomposing the complex TME from histological images into its constituent parts is crucial for evaluating its patterns and enhancing GC therapies.

A large annotated cervical cytology images dataset for AI models to aid cervical cancer screening.

Accurate detection of abnormal cervical cells in cervical cancer screening increases the chances of timely treatment. The vigorous development of deep learning methods has established a new ecosystem for cervical cancer screening, which has been proven to effectively improve efficiency and accuracy of cell detection in many studies. Although many contributing studies have been conducted, limited public datasets and time-consuming collection efforts may hinder the generalization performance of those advanced models and restrict further research.