Imagen de Portada

Accelerating Causal Network Discovery of Alzheimer Disease Biomarkers via Scientific Literature-based Retrieval Augmented Generation

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Zhou, Xiaofan, Huang, Liangjie, Cheng, Pinyang, Yin, Wenpen, Zhang, Rui, Hao, Wenrui, Cheng, Lu
Formato:	Preprint
Publicado:	2025
Materias:	Information Retrieval Quantitative Methods
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Unraveling the Biomarker Prospects of High-Altitude Diseases: Insights from Biomolecular Event Network Constructed using Text Mining
por: Bhasuran, Balu, et al.
Publicado: (2025)

Gene-associated Disease Discovery Powered by Large Language Models
por: Chang, Jiayu, et al.
Publicado: (2024)

SGUQ: Staged Graph Convolution Neural Network for Alzheimer's Disease Diagnosis using Multi-Omics Data
por: Tao, Liang, et al.
Publicado: (2024)

Learning Patient-Specific Spatial Biomarker Dynamics via Operator Learning for Alzheimer's Disease Progression
por: Wang, Jindong, et al.
Publicado: (2025)

Knowledge Graph Extraction from Biomedical Literature for Alkaptonuria Rare Disease
por: Pham, Giang, et al.
Publicado: (2026)

Graph-Based Biomarker Discovery and Interpretation for Alzheimer's Disease
por: Khalid, Maryam, et al.
Publicado: (2024)

Data-Driven Modeling of Amyloid-beta Targeted Antibodies for Alzheimer's Disease
por: Rabiei, Kobra, et al.
Publicado: (2025)

Causal Inference, Biomarker Discovery, Graph Neural Network, Feature Selection
por: Lan, Chaowang, et al.
Publicado: (2025)

Unveiling Scaling Laws of Parameter Identifiability and Uncertainty Quantification in Data-Driven Biological Modeling
por: Wang, Shun, et al.
Publicado: (2026)

A Systematic Computational Framework for Practical Identifiability Analysis in Mathematical Models Arising from Biology
por: Wang, Shun, et al.
Publicado: (2025)

MedCPT: Contrastive Pre-trained Transformers with Large-scale PubMed Search Logs for Zero-shot Biomedical Information Retrieval
por: Jin, Qiao, et al.
Publicado: (2023)

BMRetriever: Tuning Large Language Models as Better Biomedical Text Retrievers
por: Xu, Ran, et al.
Publicado: (2024)

ChemMiner: A Large Language Model Agent System for Chemical Literature Data Mining
por: Chen, Kexin, et al.
Publicado: (2024)

Autonomous Agent-Orchestrated Digital Twins (AADT): Leveraging the OpenClaw Framework for State Synchronization in Rare Genetic Disorders
por: Chen, Hongzhuo, et al.
Publicado: (2026)

ALNSynergy: a graph convolutional network with multi-representation alignment for drug synergy prediction
por: Yang, Xinxing, et al.
Publicado: (2023)

Multi-Label Classification with Generative AI Models in Healthcare: A Case Study of Suicidality and Risk Factors
por: Huang, Ming, et al.
Publicado: (2025)

AI-Driven Drug Repurposing through miRNA-mRNA Relation
por: Manoharan, Sharanya, et al.
Publicado: (2025)

Bioptic B1: A Target-Agnostic Potency-Based Small Molecules Search Engine
por: Vinogradov, Vlad, et al.
Publicado: (2024)

ProtoBERT-LoRA: Parameter-Efficient Prototypical Finetuning for Immunotherapy Study Identification
por: Zhang, Shijia, et al.
Publicado: (2025)

MS2MetGAN: Latent-space adversarial training for metabolite-spectrum matching in MS/MS database search
por: Tsai, Meng, et al.
Publicado: (2026)

BioChemInsight: An Online Platform for Automated Extraction of Chemical Structures and Activity Data from Patents
por: Wang, Zhe, et al.
Publicado: (2025)

MALADE: Orchestration of LLM-powered Agents with Retrieval Augmented Generation for Pharmacovigilance
por: Choi, Jihye, et al.
Publicado: (2024)

WGTDA: A Topological Perspective to Biomarker Discovery in Gene Expression Data
por: Nyase, Ndivhuwo, et al.
Publicado: (2024)

ORCA: A Comprehensive AI-Driven Platform for Digital Pathology Analysis and Biomarker Discovery
por: Shaker, Noor, et al.
Publicado: (2025)

Antibiotic Resistance Microbiology Dataset (ARMD): A Resource for Antimicrobial Resistance from EHRs
por: Haredasht, Fateme Nateghi, et al.
Publicado: (2025)

Accelerating Discovery of Novel and Bioactive Ligands With Pharmacophore-Informed Generative Models
por: Xie, Weixin, et al.
Publicado: (2024)

Domain Knowledge Infused Conditional Generative Models for Accelerating Drug Discovery
por: Hu, Bing, et al.
Publicado: (2025)

Biomarker Discovery with Quantum Neural Networks: A Case-study in CTLA4-Activation Pathways
por: Nguyen, Nam
Publicado: (2023)

Inhibiting Alzheimer's Disease by Targeting Aggregation of Beta-Amyloid
por: Joshi, Ananya, et al.
Publicado: (2025)

Machine Learning Classification of Alzheimer's Disease Stages Using Cerebrospinal Fluid Biomarkers Alone
por: Tiwari, Vivek Kumar, et al.
Publicado: (2024)

ECGomics: An Open Platform for AI-ECG Digital Biomarker Discovery
por: Zhang, Deyun, et al.
Publicado: (2026)

RCSB PDB AI Help Desk: retrieval-augmented generation for protein structure deposition support
por: Chithari, Vivek Reddy, et al.
Publicado: (2026)

OpenAIs HealthBench in Action: Evaluating an LLM-Based Medical Assistant on Realistic Clinical Queries
por: Ravichandran, Sandhanakrishnan, et al.
Publicado: (2025)

Discovering Multi-omic Biomarkers for Prostate Cancer Severity Using Machine Learning
por: Zhou, Jefferson, et al.
Publicado: (2024)

Enabling Few-Shot Alzheimer's Disease Diagnosis on Biomarker Data with Tabular LLMs
por: Kearney, Sophie, et al.
Publicado: (2025)

Neural Graph Matching Improves Retrieval Augmented Generation in Molecular Machine Learning
por: Wang, Runzhong, et al.
Publicado: (2025)

Mamba-SSM with LLM Reasoning for Feature Selection: Faithfulness-Aware Biomarker Discovery
por: Balan, Pushpa Kumar, et al.
Publicado: (2026)

Multimodal Alignment Improves Generalizability of Genomic Biomarker Prediction in Computational Pathology
por: Redekop, Ekaterina, et al.
Publicado: (2026)

Identifying Critical Phases for Disease Onset with Sparse Haematological Biomarkers
por: Zerio, Andrea, et al.
Publicado: (2025)

Concordance in basal cell carcinoma diagnosis. Building a proper ground truth to train Artificial Intelligence tools
por: Silva-Clavería, Francisca, et al.
Publicado: (2024)