Author

Yeju He

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Open access Aug 2026

PCMamba: Integrating partial convolution and state space models for lung cancer histopathological image classification

Highlights • PCMamba integrates Partial Convolution with State Space Models for lung cancer classification.• Achieves 94.17% accuracy and 99.28% AUC on the LungHist700 dataset.• Dual-branch design captures both local textures and long-range tissue dependencies.• Reduces computational cost by 75% while maintaining state-of-the-art performance.

Xiao-Lin Wang, Bo Chen, Yu-Han Chen et al. · Translational Oncology · 0 citations

Open access Aug 2026

Unveiling the power of TIIC: A prognostic tool for esophageal adenocarcinoma

Highlights • A novel TIIC signature score predicts esophageal adenocarcinoma prognosis with high accuracy.• Integrating 20 machine learning algorithms establishes a reliable, data-driven prognostic model.• High TIIC scores correlate with poor survival outcomes and enhanced tumor genomic instability.• TIIC signature score offers insights into immune response and immunotherapy potential for EAC patients.

Shao Gao, Bingyan Du, Yeju He et al. · Translational Oncology · 0 citations