Cover Image

The CRITICAL Records Integrated Standardization Pipeline (CRISP): End-to-End Processing of Large-scale Multi-institutional OMOP CDM Data

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Luo, Xiaolong, Li, Michael Lingzhi
Format:	Preprint
Published:	2025
Subjects:	Machine Learning I.2.6; H.2.8
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

ReaGeo: Reasoning-Enhanced End-to-End Geocoding with LLMs
by: Cui, Jian, et al.
Published: (2026)

COMET: Codebook-based Online-adaptive Multi-scale Embedding for Time-series Anomaly Detection
by: Park, Jinwoo, et al.
Published: (2026)

AI and Machine Learning Approaches for Predicting Nanoparticles Toxicity The Critical Role of Physiochemical Properties
by: Yousaf, Iqra
Published: (2024)

Simple yet Effective Node Property Prediction on Edge Streams under Distribution Shifts
by: Lee, Jongha, et al.
Published: (2025)

Are We Winning the Wrong Game? Revisiting Evaluation Practices for Long-Term Time Series Forecasting
by: Phungtua-eng, Thanapol, et al.
Published: (2026)

Analyzing the Impact of Release Season and Production Budget on Movie Revenue and Profitability
by: Torkamani, Mohammad Jalili, et al.
Published: (2026)

Survey Transfer Learning: Recycling Data with Silicon Responses
by: Amini, Ali
Published: (2025)

Prior-Aligned Data Cleaning for Tabular Foundation Models
by: Berti-Equille, Laure
Published: (2026)

The CTU Prague Relational Learning Repository
by: Motl, Jan, et al.
Published: (2015)

Stable and Privacy-Preserving Synthetic Educational Data with Empirical Marginals: A Copula-Based Approach
by: Ramos, Gabriel Diaz, et al.
Published: (2026)

Evo-DKD: Dual-Knowledge Decoding for Autonomous Ontology Evolution in Large Language Models
by: Raman, Vishal, et al.
Published: (2025)

Towards Interactively Improving ML Data Preparation Code via "Shadow Pipelines"
by: Grafberger, Stefan, et al.
Published: (2024)

Predicting and improving test-time scaling laws via reward tail-guided search
by: Li, Muheng, et al.
Published: (2026)

Illuminating Patterns of Divergence: DataDios SmartDiff for Large-Scale Data Difference Analysis
by: Poduri, Aryan, et al.
Published: (2025)

Noise or Signal? Deconstructing Contradictions and An Adaptive Remedy for Reversible Normalization in Time Series Forecasting
by: Fu, Fanzhe, et al.
Published: (2025)

FlowRL: Flow-Augmented Few-Shot Reinforcement Learning for Semi-Structured Sensor Data
by: Pivezhandi, Mohammad, et al.
Published: (2024)

LakeMLB: Data Lake Machine Learning Benchmark
by: Pan, Feiyu, et al.
Published: (2026)

Bi-View Embedding Fusion: A Hybrid Learning Approach for Knowledge Graph's Nodes Classification Addressing Problems with Limited Data
by: Napoli, Rosario, et al.
Published: (2025)

Task Memory Engine: Spatial Memory for Robust Multi-Step LLM Agents
by: Ye, Ye
Published: (2025)

Tulip Agent -- Enabling LLM-Based Agents to Solve Tasks Using Large Tool Libraries
by: Ocker, Felix, et al.
Published: (2024)

Tiny QA Benchmark++: Ultra-Lightweight, Synthetic Multilingual Dataset Generation & Smoke-Tests for Continuous LLM Evaluation
by: Koc, Vincent
Published: (2025)

SAGE: Scale-Aware Gradual Evolution for Continual Knowledge Graph Embedding
by: Li, Yifei, et al.
Published: (2025)

Learning from Preferences and Mixed Demonstrations in General Settings
by: Brown, Jason R, et al.
Published: (2025)

ScaleMAP: Preserving Local Density and Neighborhood Structure in Low-Dimensional Embeddings
by: Poorna, Rajas, et al.
Published: (2026)

AgentLTV: An Agent-Based Unified Search-and-Evolution Framework for Automated Lifetime Value Prediction
by: Wu, Chaowei, et al.
Published: (2026)

What Should LLMs Forget? Quantifying Personal Data in LLMs for Right-to-Be-Forgotten Requests
by: Staufer, Dimitri
Published: (2025)

Sketch Decompositions for Classical Planning via Deep Reinforcement Learning
by: Aichmüller, Michael, et al.
Published: (2024)

LeanProgress: Guiding Search for Neural Theorem Proving via Proof Progress Prediction
by: George, Robert Joseph, et al.
Published: (2025)

Zero-Shot Context Generalization in Reinforcement Learning from Few Training Contexts
by: Chapman, James, et al.
Published: (2025)

From Cumulative Constraints to Adaptive Runtime Safety Control for Nonstationary Reinforcement Learning
by: Tomashevskiy, Timofey
Published: (2026)

A Parallel Hybrid Action Space Reinforcement Learning Model for Real-world Adaptive Traffic Signal Control
by: Wang, Yuxuan, et al.
Published: (2025)

NeSIG: A Neuro-Symbolic Method for Learning to Generate Planning Problems
by: Núñez-Molina, Carlos, et al.
Published: (2023)

Constrained Auto-Bidding via Generative Response Modeling
by: Yang, Eunseok, et al.
Published: (2026)

Fractional Policy Gradients: Reinforcement Learning with Long-Term Memory
by: Pawar, Urvi, et al.
Published: (2025)

Learning to Select Goals in Automated Planning with Deep-Q Learning
by: Núñez-Molina, Carlos, et al.
Published: (2024)

GraphEval36K: Benchmarking Coding and Reasoning Capabilities of Large Language Models on Graph Datasets
by: Wu, Qiming, et al.
Published: (2024)

LEFT: Learnable Fusion of Tri-view Tokens for Unsupervised Time Series Anomaly Detection
by: Wang, Dezheng, et al.
Published: (2026)

HERO: Hint-Based Efficient and Reliable Query Optimizer
by: Zinchenko, Sergey, et al.
Published: (2024)

Dynamics of COVID-19 Misinformation: An Analysis of Conspiracy Theories, Fake Remedies, and False Reports
by: Thakur, Nirmalya, et al.
Published: (2025)

Selective Progress-Aware Querying for Human-in-the-Loop Reinforcement Learning
by: Muraleedharan, Anujith, et al.
Published: (2025)