activity
20242026
collaborators

7 papers

eess.IV2026

Colon-Bench: An Agentic Workflow for Scalable Dense Lesion Annotation in Full-Procedure Colonoscopy Videos

Abdullah Hamdi, Changchun Yang, Xin Gao

Early screening via colonoscopy is critical for colon cancer prevention, yet developing robust AI systems for this domain is hindered by the lack of densely annotated, long-sequenc…

cs.CV2026

Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis

Yilan Zhang, Li Nanbo, Changchun Yang +2

The integration of histology images and gene profiles has shown great promise for improving survival prediction in cancer. However, current approaches often struggle to model intra…

cs.CV2026

Perturb-and-Restore: Simulation-driven Structural Augmentation Framework for Imbalance Chromosomal Anomaly Detection

Yilan Zhang, Hanbiao Chen, Changchun Yang +10

Detecting structural chromosomal abnormalities is crucial for accurate diagnosis and management of genetic disorders. However, collecting sufficient structural abnormality data is…

q-bio.QM2025

PAST: A multimodal single-cell foundation model for histopathology and spatial transcriptomics in cancer

Changchun Yang, Haoyang Li, Yushuai Wu +8

While pathology foundation models have transformed cancer image analysis, they often lack integration with molecular data at single-cell resolution, limiting their utility for prec…

q-bio.QM2025

An Inclusive Foundation Model for Generalizable Cytogenetics in Precision Oncology

Changchun Yang, Weiqian Dai, Yilan Zhang +8

Chromosome analysis is vital for diagnosing genetic disorders and guiding cancer therapy decisions through the identification of somatic clonal aberrations. However, developing an…

eess.IV2025

Improving Representation of High-frequency Components for Medical Visual Foundation Models

Yuetan Chu, Yilan Zhang, Zhongyi Han +5

Foundation models have recently attracted significant attention for their impressive generalizability across diverse downstream tasks. However, these models are demonstrated to exh…