activity
20242026
most citedPathM3: A Multimodal Multi-Task Multiple Instance Learning Framework for Whole Slide Image Classification and Captioning

20 citations · 20 across the 4 of their papers we have counts for

collaborators

5 papers

q-bio.QM2026

scpFormer: A Foundation Model for Unified Representation and Integration of the Single-Cell Proteomics

Qifeng Zhou, Lei Yu, Yuzhi Guo +5

The integration of single-cell proteomic data is often hindered by the fragmented nature of targeted antibody panels. To address this limitation, we introduce scpFormer, a transfor…

cs.CV2025

Text-Guided Multi-Instance Learning for Scoliosis Screening via Gait Video Analysis

Haiqing Li, Yuzhi Guo, Feng Jiang +5

Early-stage scoliosis is often difficult to detect, particularly in adolescents, where delayed diagnosis can lead to serious health issues. Traditional X-ray-based methods carry ra…

cs.CV2025

Leveraging Gait Patterns as Biomarkers: An attention-guided Deep Multiple Instance Learning Network for Scoliosis Classification

Haiqing Li, Yuzhi Guo, Feng Jiang +3

Scoliosis is a spinal curvature disorder that is difficult to detect early and can compress the chest cavity, impacting respiratory function and cardiac health. Especially for adol…

cs.CV2025

Histopathology Multi-modal Embedding for Pathology Composed Retrieval

Qifeng Zhou, Wenliang Zhong, Thao M. Dang +4

To overcome the black-box nature of predictive AI and the hallucination risks of generative models, retrieval-based models offer an interpretable, evidence-based paradigm for patho…

cs.CV2024★ 20 cited

PathM3: A Multimodal Multi-Task Multiple Instance Learning Framework for Whole Slide Image Classification and Captioning

Qifeng Zhou, Wenliang Zhong, Yuzhi Guo +3

In the field of computational histopathology, both whole slide images (WSIs) and diagnostic captions provide valuable insights for making diagnostic decisions. However, aligning WS…