1 citations · 4 across the 11 of their papers we have counts for
11 papers
Tabular LLMs for Interpretable Few-Shot Alzheimer's Disease Prediction with Multimodal Biomedical Data
Sophie Kearney, Shu Yang, Zixuan Wen +8
Accurate diagnosis of Alzheimer's disease (AD) requires handling tabular biomarker data, yet such data are often small and incomplete, where deep learning models frequently fail to…
Enabling Few-Shot Alzheimer's Disease Diagnosis on Biomarker Data with Tabular LLMs
Sophie Kearney, Shu Yang, Zixuan Wen +6
Early and accurate diagnosis of Alzheimer's disease (AD), a complex neurodegenerative disorder, requires analysis of heterogeneous biomarkers (e.g., neuroimaging, genetic risk fact…
NeuroSymAD: A Neuro-Symbolic Framework for Interpretable Alzheimer's Disease Diagnosis
Yexiao He, Ziyao Wang, Yuning Zhang +4
Alzheimer's disease (AD) diagnosis is complex, requiring the integration of imaging and clinical data for accurate assessment. While deep learning has shown promise in brain MRI an…
Accessing the topological properties of human brain functional sub-circuits in Echo State Networks
Bach Nguyen, Tianlong Chen, Shu Yang +3
Recent years have witnessed an emerging trend in neuromorphic computing that centers around the use of brain connectomics as a blueprint for artificial neural networks. Connectomic…
Integrating Social Determinants of Health into Knowledge Graphs: Evaluating Prediction Bias and Fairness in Healthcare
Tianqi Shang, Weiqing He, Tianlong Chen +4
Social determinants of health (SDoH) play a crucial role in patient health outcomes, yet their integration into biomedical knowledge graphs remains underexplored. This study addres…
Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning
Abhinav Bandari, Lu Yin, Cheng-Yu Hsieh +5
Network pruning has emerged as a potential solution to make LLMs cheaper to deploy. However, existing LLM pruning approaches universally rely on the C4 dataset as the calibration d…
Leveraging Social Determinants of Health in Alzheimer's Research Using LLM-Augmented Literature Mining and Knowledge Graphs
Tianqi Shang, Shu Yang, Weiqing He +7
Growing evidence suggests that social determinants of health (SDoH), a set of nonmedical factors, affect individuals' risks of developing Alzheimer's disease (AD) and related demen…
Knowledge-Driven Feature Selection and Engineering for Genotype Data with Large Language Models
Joseph Lee, Shu Yang, Jae Young Baik +8
Predicting phenotypes with complex genetic bases based on a small, interpretable set of variant features remains a challenging task. Conventionally, data-driven approaches are util…
SDoH-GPT: Using Large Language Models to Extract Social Determinants of Health (SDoH)
Bernardo Consoli, Xizhi Wu, Song Wang +10
Extracting social determinants of health (SDoH) from unstructured medical notes depends heavily on labor-intensive annotations, which are typically task-specific, hampering reusabi…
A principled framework to assess the information-theoretic fitness of brain functional sub-circuits
Duy Duong-Tran, Nghi Nguyen, Shizhuo Mu +10
In systems and network neuroscience, many common practices in brain connectomic analysis are often not properly scrutinized. One such practice is mapping a predetermined set of sub…
(PASS) Visual Prompt Locates Good Structure Sparsity through a Recurrent HyperNetwork
Tianjin Huang, Fang Meng, Li Shen +5
Large-scale neural networks have demonstrated remarkable performance in different domains like vision and language processing, although at the cost of massive computation resources…