Imagen de Portada

Leveraging Foundation Language Models (FLMs) for Automated Cohort Extraction from Large EHR Databases

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Mugambi, Purity, Meliou, Alexandra, Fiterau, Madalina
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Zero-shot Microclimate Prediction with Deep Learning
por: Deznabi, Iman, et al.
Publicado: (2024)

FeatEHR-LLM: Leveraging Large Language Models for Feature Engineering in Electronic Health Records
por: Karami, Hojjat, et al.
Publicado: (2026)

Metadata Extraction Leveraging Large Language Models
por: Han, Cuize, et al.
Publicado: (2025)

Exploring Scaling Laws for EHR Foundation Models
por: Zhang, Sheng, et al.
Publicado: (2025)

Integrating Genomics into Multimodal EHR Foundation Models
por: Amar, Jonathan, et al.
Publicado: (2025)

Challenges in Understanding Modality Conflict in Vision-Language Models
por: Nguyen, Trang, et al.
Publicado: (2025)

Leveraging Language Models for Automated Patient Record Linkage
por: Beheshti, Mohammad, et al.
Publicado: (2025)

Customizing Open Source LLMs for Quantitative Medication Attribute Extraction across Heterogeneous EHR Systems
por: Fei, Zhe, et al.
Publicado: (2025)

Resolution-Aware Retrieval Augmented Zero-Shot Forecasting
por: Deznabi, Iman, et al.
Publicado: (2025)

ProtoEHR: Hierarchical Prototype Learning for EHR-based Healthcare Predictions
por: Cai, Zi, et al.
Publicado: (2025)

EHR-RAGp: Retrieval-Augmented Prototype-Guided Foundation Model for Electronic Health Records
por: Shurrab, Saeed, et al.
Publicado: (2026)

Foundations of Large Language Models
por: Xiao, Tong, et al.
Publicado: (2025)

Leveraging Generic Time Series Foundation Models for EEG Classification
por: Gnassounou, Théo, et al.
Publicado: (2025)

What Level of Automation is "Good Enough"? A Benchmark of Large Language Models for Meta-Analysis Data Extraction
por: Li, Lingbo, et al.
Publicado: (2025)

Fine-tuning Large Language Model for Automated Algorithm Design
por: Liu, Fei, et al.
Publicado: (2025)

Automated Attention Pattern Discovery at Scale in Large Language Models
por: Katzy, Jonathan, et al.
Publicado: (2026)

Leveraging Large Language Models for Web Scraping
por: Ahluwalia, Aman, et al.
Publicado: (2024)

Leveraging Large Language Models for enzymatic reaction prediction and characterization
por: Di Fruscia, Lorenzo, et al.
Publicado: (2025)

Leveraging Intermediate Representations of Time Series Foundation Models for Anomaly Detection
por: Han, Chan Sik, et al.
Publicado: (2025)

Griffin: Towards a Graph-Centric Relational Database Foundation Model
por: Wang, Yanbo, et al.
Publicado: (2025)

The Structural Scalpel: Automated Contiguous Layer Pruning for Large Language Models
por: Lu, Yao, et al.
Publicado: (2025)

ACES: Automatic Cohort Extraction System for Event-Stream Datasets
por: Xu, Justin, et al.
Publicado: (2024)

Automating the Enterprise with Foundation Models
por: Wornow, Michael, et al.
Publicado: (2024)

IVP-VAE: Modeling EHR Time Series with Initial Value Problem Solvers
por: Xiao, Jingge, et al.
Publicado: (2023)

Neuron-Anchored Rule Extraction for Large Language Models via Contrastive Hierarchical Ablation
por: Sovrano, Francesco, et al.
Publicado: (2026)

Token-Efficient Leverage Learning in Large Language Models
por: Zeng, Yuanhao, et al.
Publicado: (2024)

Leveraging Foundational Models and Simple Fusion for Multi-modal Physiological Signal Analysis
por: Ghallab, Youssef, et al.
Publicado: (2025)

ChronosAD: Leveraging Time Series Foundation Models for Accurate Anomaly Detection
por: Khan, Uzair, et al.
Publicado: (2026)

Automated Federated Pipeline for Parameter-Efficient Fine-Tuning of Large Language Models
por: Fang, Zihan, et al.
Publicado: (2024)

Leveraging Large Language Models for Effective Label-free Node Classification in Text-Attributed Graphs
por: Zhang, Taiyan, et al.
Publicado: (2024)

Amber Pruner: Leveraging N:M Activation Sparsity for Efficient Prefill in Large Language Models
por: An, Tai, et al.
Publicado: (2025)

A Survey on Model Extraction Attacks and Defenses for Large Language Models
por: Zhao, Kaixiang, et al.
Publicado: (2025)

CIRCUITSYNTH: Leveraging Large Language Models for Circuit Topology Synthesis
por: Vijayaraghavan, Prashanth, et al.
Publicado: (2024)

Leveraging Machine Learning for Early Autism Detection via INDT-ASD Indian Database
por: Shrivastava, Trapti, et al.
Publicado: (2024)

EvoEngineer: Mastering Automated CUDA Kernel Code Evolution with Large Language Models
por: Guo, Ping, et al.
Publicado: (2025)

An Automated Survey of Generative Artificial Intelligence: Large Language Models, Architectures, Protocols, and Applications
por: Garrido-Merchán, Eduardo C., et al.
Publicado: (2023)

EEGAgent: A Unified Framework for Automated EEG Analysis Using Large Language Models
por: Zhao, Sha, et al.
Publicado: (2025)

Creating Artificial Students that Never Existed: Leveraging Large Language Models and CTGANs for Synthetic Data Generation
por: Khalil, Mohammad, et al.
Publicado: (2025)

Generating Multi-Table Time Series EHR from Latent Space with Minimal Preprocessing
por: Cho, Eunbyeol, et al.
Publicado: (2025)

An Automated Reinforcement Learning Reward Design Framework with Large Language Model for Cooperative Platoon Coordination
por: Wei, Dixiao, et al.
Publicado: (2025)