Papers Data Integration
“Data Integration” 태그가 달린 논문 431편 · 필터 해제
Urban Representation Learning for Fine-grained Economic Mapping: A Semi-supervised Graph-based Approach
Fine-grained economic mapping through urban representation learning has emerged as a crucial tool for evidence-based economic decisions. While existing methods primarily rely on supervised or unsupervised approaches, the…
Data IntegrationGraph LearningMulti-Task LearningRepresentation LearningTUM2TWIN: Introducing the Large-Scale Multimodal Urban Digital Twin Benchmark Dataset
Urban Digital Twins (UDTs) have become essential for managing cities and integrating complex, heterogeneous data from diverse sources. Creating UDTs involves challenges at multiple process stages, including acquiring acc…
Data IntegrationNeRFNovel View SynthesisSemantic SegmentationCrashSage: A Large Language Model-Centered Framework for Contextual and Interpretable Traffic Crash Analysis
Road crashes claim over 1.3 million lives annually worldwide and incur global economic losses exceeding \$1.8 trillion. Such profound societal and financial impacts underscore the urgent need for road safety research tha…
Data AugmentationData IntegrationFew-Shot LearningLanguage Modeling+2CDE-Mapper: Using Retrieval-Augmented Language Models for Linking Clinical Data Elements to Controlled Vocabularies
The standardization of clinical data elements (CDEs) aims to ensure consistent and comprehensive patient information across various healthcare systems. Existing methods often falter when standardizing CDEs of varying rep…
Data IntegrationIn-Context LearningPrompt EngineeringRetrieval-augmented GenerationInterpretable graph-based models on multimodal biomedical data integration: A technical review and benchmarking
Integrating heterogeneous biomedical data including imaging, omics, and clinical records supports accurate diagnosis and personalised care. Graph-based models fuse such non-Euclidean data by capturing spatial and relatio…
BenchmarkingData Integrationgraph constructionGraph Learning+1Multimodal Doctor-in-the-Loop: A Clinically-Guided Explainable Framework for Predicting Pathological Response in Non-Small Cell Lung Cancer
This study proposes a novel approach combining Multimodal Deep Learning with intrinsic eXplainable Artificial Intelligence techniques to predict pathological response in non-small cell lung cancer patients undergoing neo…
Data IntegrationDeep LearningExplainable artificial intelligenceMultimodal Deep LearningDeep Multi-modal Breast Cancer Detection Network
Automated breast cancer detection via computer vision techniques is challenging due to the complex nature of breast tissue, the subtle appearance of cancerous lesions, and variations in breast density. Mainstream techniq…
Breast Cancer DetectionData IntegrationDiagnosticLeveraging Language Models for Automated Patient Record Linkage
Objective: Healthcare data fragmentation presents a major challenge for linking patient data, necessitating robust record linkage to integrate patient records from diverse sources. This study investigates the feasibility…
BlockingData IntegrationSentence EmbeddingsGeneralized probabilistic canonical correlation analysis for multi-modal data integration with full or partial observations
Background: The integration and analysis of multi-modal data are increasingly essential across various domains including bioinformatics. As the volume and complexity of such data grow, there is a pressing need for comput…
ClusteringData IntegrationDimensionality ReductionMissing ValuesSimplifying Data Integration: SLM-Driven Systems for Unified Semantic Queries Across Heterogeneous Databases
The integration of heterogeneous databases into a unified querying framework remains a critical challenge, particularly in resource-constrained environments. This paper presents a novel Small Language Model(SLM)-driven s…
Data IntegrationLanguage ModelingLanguage ModellingQuestion Answering+4OmniEcon Nexus: Global Microeconomic Simulation Engine
OmniEcon Nexus is an open-source, high-performance simulation engine for global microeconomic and macroeconomic analysis. Built with advanced deep learning, agent-based modeling, and optimization techniques, it enables d…
Data IntegrationPortfolio OptimizationQ-LearningThe challenge of uncertainty quantification of large language models in medicine
This study investigates uncertainty quantification in large language models (LLMs) for medical applications, emphasizing both technical innovations and philosophical implications. As LLMs become integral to clinical deci…
Bayesian InferenceData IntegrationDecision MakingMeta-Learning+1Cross-Asset Risk Management: Integrating LLMs for Real-Time Monitoring of Equity, Fixed Income, and Currency Markets
Large language models (LLMs) have emerged as powerful tools in the field of finance, particularly for risk management across different asset classes. In this work, we introduce a Cross-Asset Risk Management framework tha…
ArticlesData IntegrationDecision MakingManagementFrom Automation to Autonomy in Smart Manufacturing: A Bayesian Optimization Framework for Modeling Multi-Objective Experimentation and Sequential Decision Making
Discovering novel materials with desired properties is essential for driving innovation. Industry 4.0 and smart manufacturing have promised transformative advances in this area through real-time data integration and auto…
Bayesian OptimizationData IntegrationDecision MakingEfficient Exploration+1A Systematic Decade Review of Trip Route Planning with Travel Time Estimation based on User Preferences and Behavior
This paper systematically explores the advancements in adaptive trip route planning and travel time estimation (TTE) through Artificial Intelligence (AI). With the increasing complexity of urban transportation systems, t…
Data IntegrationFederated LearningMeta-LearningReinforcement Learning (RL)+1Multimodal Data Integration for Sustainable Indoor Gardening: Tracking Anyplant with Time Series Foundation Model
Indoor gardening within sustainable buildings offers a transformative solution to urban food security and environmental sustainability. By 2030, urban farming, including Controlled Environment Agriculture (CEA) and verti…
Data IntegrationPlant PhenotypingTime SeriesMulti-dataset and Transfer Learning Using Gene Expression Knowledge Graphs
Gene expression datasets offer insights into gene regulation mechanisms, biochemical pathways, and cellular functions. Additionally, comparing gene expression profiles between disease and control patients can deepen the …
Data IntegrationGraph EmbeddingGraph Neural NetworkKnowledge Graph Embedding+2Federated Learning: A new frontier in the exploration of multi-institutional medical imaging data
Artificial intelligence has transformed the perspective of medical imaging, leading to a genuine technological revolution in modern computer-assisted healthcare systems. However, ubiquitously featured deep learning (DL) …
Data IntegrationFederated LearningMODIS: Multi-Omics Data Integration for Small and Unpaired Datasets
A key challenge today lies in the ability to efficiently handle multi-omics data since such multimodal data may provide a more comprehensive overview of the underlying processes in a system. Yet it comes with challenges:…
Data IntegrationGridMind: A Multi-Agent NLP Framework for Unified, Cross-Modal NFL Data Insights
The rapid growth of big data and advancements in computational techniques have significantly transformed sports analytics. However, the diverse range of data sources -- including structured statistics, semi-structured fo…
ArticlesData IntegrationRAGRepresentation Learning+3