合作项目

LBP

We have established a cooperative relationship with LBP Group to develop an intelligent labeling tool for pathological images for problems.

Peking Union Medical College

In cooperation with Peking Union Medical College and Shenzhen Maternal and Child Health Hospital, the intelligent interpretation system is designed to improve the understanding of colposcopy reports.

Peking Union Medical College

We cooperated with Peking Union Medical College and Shenzhen Maternal and Child Health Hospital to develop an efficient and accurate artificial intelligence diagnosis system for cervical cancer omics pathological images.

Wuhan Tongji Hospital

The collaboration focuses on exploring the recurrence patterns of liver cancer based on liver WSI slices.

The First Affiliated Hospital of Sun Yat-sen University (Nansha)

This project aims to develop a multimodal AI model for predicting the efficacy of various drug therapies in treating GER symptoms.

Hebei Medical University Fourth Hospital

The project is predicting the mutation status of the PIK3CA gene based on HE slices and the efficacy of neoadjuvant therapy.

Hebei Medical University Fourth Hospital

a multi-modal deep learning model based on HE images and HER2 immunohistochemistry images for predicting the prognosis of metastatic breast cancer.

Hebei Medical University Fourth Hospital

We jointly dedicated to researching the application of artificial intelligence in the field of breast cancer.

Sixth Affiliated Hospital of Sun Yat-sen University

Our laboratory is collaborating with The Sixth Affiliated Hospital of Sun Yat-sen University (SYSU Sixth Hospital) to develop an intelligent multi-modal medical data platform.

Zhejiang Cancer Hospital

Lung cancer is the most common and diverse type of cancer in modern society. This project focuses on case-level lung cancer tasks that require comprehensive judgment based on multiple slices, particularly the task of evaluating the immunohistochemical heterogeneity of lung cancer. It develops report generation and diagnostic assistance models to support pathologists in making case-level diagnoses.