89 citations · 169 across the 21 of their papers we have counts for
21 papers
A World Model of Radiologist Reading for Medical Image Representation Learning
Yiwei Li, Zihao Wu, Huaqin Zhao +5
Radiologist eye-tracking data provide a rich record of how experts search, compare, and accumulate evidence during image reading; yet, existing methods exploit this signal only par…
Learning Cross-Atlas Consistent Brain Disorder Representations via Disentangled Multi-Atlas Functional Connectivity Learning
Minheng Chen, Chao Cao, Jing Zhang +2
Functional connectivity (FC) derived from resting-state fMRI is widely used to characterize large-scale brain network alterations in neurological and psychiatric disorders. However…
Probability-Invariant Random Walk Learning on Gyral Folding-Based Cortical Similarity Networks for Alzheimer's and Lewy Body Dementia Diagnosis
Minheng Chen, Tong Chen, Chao Cao +4
Alzheimer's disease (AD) and Lewy body dementia (LBD) present overlapping clinical features yet require distinct diagnostic strategies. While neuroimaging-based brain network analy…
Community-Level Modeling of Gyral Folding Patterns for Robust and Anatomically Informed Individualized Brain Mapping
Minheng Chen, Tong Chen, Yan Zhuang +5
Cortical folding exhibits substantial inter-individual variability while preserving stable anatomical landmarks that enable fine-scale characterization of cortical organization. Am…
Large Language Models for Assisting American College Applications
Zhengliang Liu, Weihang You, Peng Shu +14
American college applications require students to navigate fragmented admissions policies, repetitive and conditional forms, and ambiguous questions that often demand cross-referen…
Gyral-Sulcal-Net: An Integrated Network Representation of Brain Folding Patterns
Chao Cao, Tong Chen, Nan Zhao +7
Our brain functions as a complex communication network, and studying it from a network perspective offers valuable insights into its organizational principles and links to cognitiv…
DCMM-Transformer: Degree-Corrected Mixed-Membership Attention for Medical Imaging
Huimin Cheng, Xiaowei Yu, Shushan Wu +7
Medical images exhibit latent anatomical groupings, such as organs, tissues, and pathological regions, that standard Vision Transformers (ViTs) fail to exploit. While recent work l…
Bridging Brain Connectomes and Clinical Reports for Early Alzheimer's Disease Diagnosis
Jing Zhang, Xiaowei Yu, Minheng Chen +8
Integrating brain imaging data with clinical reports offers a valuable opportunity to leverage complementary multimodal information for more effective and timely diagnosis in pract…
Domain-Adaptive Diagnosis of Lewy Body Disease with Transferability Aware Transformer
Xiaowei Yu, Jing Zhang, Tong Chen +8
Lewy Body Disease (LBD) is a common yet understudied form of dementia that imposes a significant burden on public health. It shares clinical similarities with Alzheimer's disease (…
GyralNet Subnetwork Partitioning via Differentiable Spectral Modularity Optimization
Yan Zhuang, Minheng Chen, Chao Cao +7
Understanding the structural and functional organization of the human brain requires a detailed examination of cortical folding patterns, among which the three-hinge gyrus (3HG) ha…
Core-Periphery Principle Guided State Space Model for Functional Connectome Classification
Minheng Chen, Xiaowei Yu, Jing Zhang +7
Understanding the organization of human brain networks has become a central focus in neuroscience, particularly in the study of functional connectivity, which plays a crucial role…
BrainNet-MoE: Brain-Inspired Mixture-of-Experts Learning for Neurological Disease Identification
Jing Zhang, Xiaowei Yu, Tong Chen +8
The Lewy body dementia (LBD) is the second most common neurodegenerative dementia after Alzheimer's disease (AD). Early differentiation between AD and LBD is crucial because they r…
Classification of Mild Cognitive Impairment Based on Dynamic Functional Connectivity Using Spatio-Temporal Transformer
Jing Zhang, Yanjun Lyu, Xiaowei Yu +7
Dynamic functional connectivity (dFC) using resting-state functional magnetic resonance imaging (rs-fMRI) is an advanced technique for capturing the dynamic changes of neural activ…
Brain-Adapter: Enhancing Neurological Disorder Analysis with Adapter-Tuning Multimodal Large Language Models
Jing Zhang, Xiaowei Yu, Yanjun Lyu +7
Understanding brain disorders is crucial for accurate clinical diagnosis and treatment. Recent advances in Multimodal Large Language Models (MLLMs) offer a promising approach to in…
Using Structural Similarity and Kolmogorov-Arnold Networks for Anatomical Embedding of Cortical Folding Patterns
Minheng Chen, Chao Cao, Tong Chen +7
The 3-hinge gyrus (3HG) is a newly defined folding pattern, which is the conjunction of gyri coming from three directions in cortical folding. Many studies demonstrated that 3HGs c…
Evaluation of OpenAI o1: Opportunities and Challenges of AGI
Tianyang Zhong, Zhengliang Liu, Yi Pan +74
This comprehensive study evaluates the performance of OpenAI's o1-preview large language model across a diverse array of complex reasoning tasks, spanning multiple domains, includi…
GP-GPT: Large Language Model for Gene-Phenotype Mapping
Yanjun Lyu, Zihao Wu, Lu Zhang +11
Pre-trained large language models(LLMs) have attracted increasing attention in biomedical domains due to their success in natural language processing. However, the complex traits a…
Holistic Evaluation of GPT-4V for Biomedical Imaging
Zhengliang Liu, Hanqi Jiang, Tianyang Zhong +47
In this paper, we present a large-scale evaluation probing GPT-4V's capabilities and limitations for biomedical image analysis. GPT-4V represents a breakthrough in artificial gener…
Evaluating Large Language Models for Radiology Natural Language Processing
Zhengliang Liu, Tianyang Zhong, Yiwei Li +43
The rise of large language models (LLMs) has marked a pivotal shift in the field of natural language processing (NLP). LLMs have revolutionized a multitude of domains, and they hav…
Exploring the Trade-Offs: Unified Large Language Models vs Local Fine-Tuned Models for Highly-Specific Radiology NLI Task
Zihao Wu, Lu Zhang, Chao Cao +12
Recently, ChatGPT and GPT-4 have emerged and gained immense global attention due to their unparalleled performance in language processing. Despite demonstrating impressive capabili…
DeID-GPT: Zero-shot Medical Text De-Identification by GPT-4
Zhengliang Liu, Yue Huang, Xiaowei Yu +15
The digitization of healthcare has facilitated the sharing and re-using of medical data but has also raised concerns about confidentiality and privacy. HIPAA (Health Insurance Port…