activity
20232026
most citedLabel-Efficient Deep Learning in Medical Image Analysis: Challenges and Future Directions

10 citations · 21 across the 14 of their papers we have counts for

collaborators
Showing 2025Show all

7 papers · 1 filter

cs.LG2025

Investigating Data Pruning for Pretraining Biological Foundation Models at Scale

Yifan Wu, Jiyue Jiang, Xichen Ye +9

Biological foundation models (BioFMs), pretrained on large-scale biological sequences, have recently shown strong potential in providing meaningful representations for diverse down…

eess.IV2025

A Versatile Pathology Co-pilot via Reasoning Enhanced Multimodal Large Language Model

Zhe Xu, Ziyi Liu, Junlin Hou +13

Multimodal large language models (MLLMs) have emerged as powerful tools for computational pathology, offering unprecedented opportunities to integrate pathological images with lang…

cs.CV2025

LLM-driven Medical Report Generation via Communication-efficient Heterogeneous Federated Learning

Haoxuan Che, Haibo Jin, Zhengrui Guo +3

LLMs have demonstrated significant potential in Medical Report Generation (MRG), yet their development requires large amounts of medical image-report pairs, which are commonly scat…

cs.CV2025

Genome-Anchored Foundation Model Embeddings Improve Molecular Prediction from Histology Images

Cheng Jin, Fengtao Zhou, Yunfang Yu +13

Precision oncology requires accurate molecular insights, yet obtaining these directly from genomics is costly and time-consuming for broad clinical use. Predicting complex molecula…

cs.CV2025★ 3 cited

PathBench: A comprehensive comparison benchmark for pathology foundation models towards precision oncology

Jiabo Ma, Yingxue Xu, Fengtao Zhou +23

The emergence of pathology foundation models has revolutionized computational histopathology, enabling highly accurate, generalized whole-slide image analysis for improved cancer d…

cs.CV2025

Discovering Pathology Rationale and Token Allocation for Efficient Multimodal Pathology Reasoning

Zhe Xu, Cheng Jin, Yihui Wang +2

Multimodal pathological image understanding has garnered widespread interest due to its potential to improve diagnostic accuracy and enable personalized treatment through integrate…

q-bio.QM2025★ 1 cited

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation

Hao Jiang, Cheng Jin, Huangjing Lin +15

Cervical cancer is a leading malignancy in female reproductive system. While AI-assisted cytology offers a cost-effective and non-invasive screening solution, current systems strug…