6 papers
STAIL: Semantic Text-Anchored Incremental Learning for Medical Imaging via Large Language Models
Songpan Gao, Yajie Zhang, Guanxing Chen +9
Deep learning models applied to medical image analysis suffer from severe catastrophic forgetting when continually adapting to new clinical tasks in dynamic environments. Mainstrea…
QM-ToT: A Medical Tree of Thoughts Reasoning Framework for Quantized Model
Zongxian Yang, Jiayu Qian, Kay Chen Tan +4
Large language models (LLMs) face significant challenges in specialized biomedical tasks due to the inherent complexity of medical reasoning and the sensitive nature of clinical da…
AbLWR:A Context-Aware Listwise Ranking Framework for Antibody-Antigen Binding Affinity Prediction via Positive-Unlabeled Learning
Fan Xu, Zhi-an Huang, Haohuai He +5
Accurate prediction of antibody-antigen binding affinity is fundamental to therapeutic design, yet remains constrained by severe label sparsity and the complexity of antigenic vari…
scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis
Yu-An Huang, Yao Hu, Yue-Chao Li +5
Functional MRI (fMRI) and single-cell transcriptomics are pivotal in Alzheimer's disease (AD) research, each providing unique insights into neural function and molecular mechanisms…
Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data
Yu-An Huang, Yue-Chao Li, Hai-Ru You +5
The exploration of cellular heterogeneity within the tumor microenvironment (TME) via single-cell RNA sequencing (scRNA-seq) is essential for understanding cancer progression and r…
scGSDR: Harnessing Gene Semantics for Single-Cell Pharmacological Profiling
Yu-An Huang, Xiyue Cao, Zhu-Hong You +3
The rise of single-cell sequencing technologies has revolutionized the exploration of drug resistance, revealing the crucial role of cellular heterogeneity in advancing precision m…