Work

Contrastive Pretraining for Computational Pathology with Visual-Language Models

Year: 2025

Type: conference-paper

Source: IEEE International Symposium on Biomedical Imaging (ISBI)

DOI: 10.1109/isbi60581.2025.10981180

Authors: Qifeng Zhou, Thao M. Dang, Yuzhi Guo, Hehuan Ma, Wenliang Zhong, Saiyang Na, Jean Gao, Junzhou Huang

Institution: The University of Texas at Arlington

Language: English

Topic: Multimodal Machine Learning Applications

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: closed

Funders: National Science Foundation, Cancer Prevention and Research Institute of Texas

Awards: Developing knowledge guided deep learning models to predict the binding between T cell receptors and neoantigens for facilitating TCR-T therapies, EAGER: Integrating Multi-Omics Biological Networks and Ontologies for lncRNA Function Annotation using Deep Learning

OpenAlex ID: W4410295449

FWCI: 0.781

Cites: 7

Cited by: 1

Related to: 10