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Yefeng Zheng

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Open access Aug 2026

An explainable biomedical foundation model via large-scale concept-enhanced vision-language pretraining.

Across a large-scale benchmark covering 78 datasets in 10 imaging modalities, ConceptCLIP demonstrates superior diagnostic performance while providing human-understandable explanations, and represents a critical milestone towards the widespread clinical adoption of AI.

Yuxiang Nie, Sunan He, Yequan Bie et al. · 0 citations
Open access Sep 2026

Structure-guided prior-driven implicit neural representations for time-of-flight PET image reconstruction

The proposed approach integrates implicit neural representations with physics-consistent modeling and prior-guided regularization, providing an effective unsupervised framework for TOF-PET reconstruction and highlighting the potential of neural field representations for tomographic imaging.

Yu-Lin Zhang, Yuxuan Long, Hong Wang et al. · 0 citations
Sep 2026

Comorbidity-Aware Radiology Report Generation.

Chest X-ray report generation systems are valuable for assisting disease diagnosis and improving healthcare efficiency. However, existing methods still face two key challenges. First, multiple diseases often co-occur, leading to a combinatorial explosion of label combinations and sparse supervision for learning a gener...

Hong-Ze Zhu, Hong Liu, Ya-Wen Huang et al. · 0 citations
Book Open access Aug 2026

PRIME: A Pretrained Representation-Induced Model for 3D Molecules in De Novo Binder Design

Biomolecular binder design for peptides and antibodies requires generating diverse candidates that satisfy stringent three-dimensional geometric constraints while enabling affinity-oriented exploration under strong structural priors. In current generative models, the effective search space for structurally feasible bin...

Zhihua Tian, Jia-Le Zhou, Ru-Bo Wang et al. · 0 citations
Book Open access Aug 2026

PRIME: A Pretrained Representation-Induced Model for 3D Molecules in De Novo Binder Design

Semantics-Preserving Exploratory Sampling (SPES), which integrates Graph Laplacian Spectral Noise to respect chain connectivity and Conditional Freedom Modulation to dynamically balance exploration with fidelity, enables diversity-enhanced generation without sacrificing geometric validity under the reported structural...

Zhihua Tian, Jiale Zhou, Rubo Wang et al. · 0 citations

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