Medical Data Processing and Analysis
Research on using LLMs for processing, augmenting, and analyzing medical datasets
Medical Data Processing and Analysis
Research on Large Language Models in Medical Data Processing and Analysis
Reimagining Missing Data Solutions
Using Language Models for Contextual Data Imputation
Enhancing Tabular Data Augmentation with AI
Using Reinforcement Learning to Improve LLM-Generated Synthetic Data
GenoTEX: Automating Genomic Analysis
LLM Agents for Efficient Disease-Gene Identification
MedTrinity-25M: Revolutionizing Medical AI
A landmark 25M+ image dataset with multi-level annotations across 10 medical modalities
Cell Ontology-Enhanced AI for Transcriptome Analysis
Leveraging biological hierarchies to improve gene expression models
TimeDiT: Transforming Time Series Analysis
A foundation model approach to handle complex temporal data
SynSUM: Bridging the Medical Data Gap
A synthetic benchmark connecting clinical notes with structured patient data
LanHAR: Bridging the Gap in Activity Recognition
Using Language Models to Interpret Sensor Data Across Diverse Environments
Leveraging LLMs to Decode Genetic Data
AI-powered feature selection for improved phenotype prediction
Bridging the Gap in Time Series Analysis
Advancing foundation models for diverse time series data across domains
SensorLLM: Bridging Language Models and Activity Recognition
Teaching LLMs to understand human movement through sensor data
Unlocking Hidden Patterns in Biological Data
Exploring Sparse Autoencoders for Interpretable Biological Insights
AI-Powered Optimization: Breaking Barriers
Training LLMs to define and solve complex optimization problems autonomously
Smarter Data Augmentation with AI
Using LLMs to optimize data augmentation strategies
AI as Biomedical Data Scientists?
Evaluating LLMs for real-world biomedical data analysis tasks
Unlocking Patient Feedback with AI
Using Large Language Models to Analyze Unstructured Patient Comments
Optimizing Research with LLM Assistance
Strategic AI Integration for Better Information Retrieval Evaluation
Unlocking Clinical Trial Data with AI
How ALIGN Uses LLMs to Solve Medical Coding Challenges
Revolutionizing Qualitative Research with AI
How Large Language Models are transforming data analysis across domains
Revolutionizing Time Series Analysis with LLMs
A training-free approach using tabular representations
The OCR Bottleneck in RAG Systems
How OCR errors cascade through knowledge retrieval pipelines
Mapping the AI4Science Landscape
Bridging the Gap Between AI and Scientific Communities
Making AI Reasoning Transparent in Table QA
Novel Plan-of-SQLs approach for interpretable table question answering
Verifying Clinical AI: A Step-by-Step Approach
Using Process-Supervised Reward Models to Enhance LLM-Generated Medical Documentation
Agentic RAG: The Next Evolution of AI Systems
Enhancing LLMs with Dynamic Data Retrieval and Autonomous Capabilities
Diffusion Models: Revolutionizing Anomaly Detection
Advanced AI for identifying threats across critical domains
Open Source LLMs for Medical Documentation
Evaluating AI-powered automation for tumor documentation in Germany
LEADS: AI-Powered Medical Literature Mining
A foundation model transforming evidence-based medicine
Unlocking Medical Data with AI
Transforming unstructured clinical notes into structured data
AI-Powered Medical Research Analysis
Using LLMs to Enhance Brain Injury Research Through Systematic Review
LLMs as Few-Shot Time Series Classifiers
Overcoming data scarcity in industrial time series analysis
AI-Powered Medical Data Extraction
Zero-shot abstraction of unstructured clinical text using frontier models
AI-Powered Thematic Analysis in Healthcare
Using LLMs to Scale Transcript Analysis for Pediatric Heart Disease Research
Making LLMs Work with Real-World Event Data
A Novel Approach for Analyzing Irregular Time-Based Events
Efficient Multimodal AI for Resource-Constrained Settings
Domain adaptation through contrastive learning for healthcare applications
PalimpChat: AI Analytics Made Interactive
Turning complex AI workflows into conversational interfaces
Self-Improving AI Teams
Bootstrapping multi-agent systems through reasoning-driven optimization
Zero-Shot LLMs vs. Crowdsourcing for Public Health
Enhancing efficiency and accuracy in social media health data labeling
Time2Lang: Bridging AI Models for Health Sensing
A novel approach connecting time series data with language models
Data Quality's Critical Impact on Healthcare AI
How textual data errors affect ML model performance in medical settings
Explainable Data Narration System
Transforming raw data into trustworthy natural language insights
Synthetic Neurosurgical Data with LLMs
Zero-shot generation to overcome clinical data limitations
Smarter Feature Selection with LLM-Lasso
Combining AI language models with statistical regression for enhanced predictive power
Evaluating LLMs for Medical Quality Control
A Chinese Benchmark for Healthcare Assessment
JoLT: Enhancing Tabular Data Analysis with LLMs
A novel approach for joint probabilistic predictions on structured data
AI-Powered Detection of Clinical Trial Data Sharing
Using language models to identify available medical research data
Smart LLM Agents for Health Monitoring
Improving heart rate analysis from wearable device data
AI-Powered Memory Assessment
Automating event segmentation to evaluate cognitive health
Unlocking Graph Data Potential with LLMs
A democratized approach for augmenting graph data through latent knowledge graphs
Decoding the Visual Brain with AI
Using LLMs to Interpret Neural Activity in the Visual Cortex
Optimizing RAG Systems
How context size and model selection impact retrieval-augmented generation
Improving Lossless Image Compression with LLMs
Bridging the gap between language models and visual data
Mojito: Revolutionizing Motion Sensing
Harnessing IMUs and LLMs for Enhanced Human Movement Analysis
Real-time Economic Shock Monitoring
Leveraging LLMs to analyze company websites for crisis response
Leveraging LLMs for Medical Data Intelligence
Transforming Electronic Health Records into Powerful Predictive Tools
Optimizing LLM Survey Simulations
Finding the right balance in synthetic data generation
Decoding Visual Hallucinations with AI
Using LLMs to analyze subjective experiences of light-induced visual phenomena
Simulating Human Movement with AI
LLMs as a privacy-preserving solution for mobility modeling
ICU-BERT: Transforming Critical Care Data Analysis
A specialized AI model for complex intensive care unit data
The Hidden Bias in Medical AI
How Patient Non-Adherence Distorts ML Models in Healthcare
Foundation Models for EEG Analysis
Evaluating large language models as feature extractors for brain data
AI-Powered Patient Cohort Generation
Automating SQL queries from clinical criteria with LLMs
AI-Powered Biological Discovery
Leveraging Language Models to Guide Perturbation Experiments
BixBench: Evaluating AI Agents in Computational Biology
First comprehensive benchmark for LLM-based biological research assistants
AI-Powered Disaster Response Systems
Using Multi-Agent LLM Frameworks for Air Quality Analysis During Wildfires
TimeXL: Smarter Time Series Prediction
Enhancing predictions with multi-modal data and LLM-powered explanations
Optimizing Multimodal AI Systems
A framework for intelligent modality selection in resource-constrained environments
AI-Generated Activity Data for Alzheimer's Research
Using LLMs to Overcome Data Scarcity in AD Monitoring
Unlocking Time Series Intelligence
A Multi-Task Question Answering Framework for Temporal Data
Edge-Ready AI: The Shakti SLM Series
Bringing specialized language models to resource-constrained devices
Smart Sample Selection for Medical LLMs
A choice-based greedy approach to enhance model performance while reducing training costs
AI Revolution in Medical Records
Cutting-edge innovations transforming healthcare in 2024
Testing LLMs with Uncommon Medical Cases
A new benchmark for real-world clinical challenges
Uncertainty-Aware AI Vision & Reasoning
Enhancing multimodal LLMs with confidence-based decision making
Standardizing Medical Fundus Reports with AI
Using LLMs to overcome standardization challenges in clinical diagnostics
Enhancing Time Series Forecasting with LLMs
Leveraging temporal patterns and semantics for superior predictions
Revolutionizing Time-Series Analysis with AI
A breakthrough approach combining time-series data with natural language reasoning
OPTIMUS: AI-Powered Alzheimer's Prediction
Using multi-modal data to predict multiple Alzheimer's outcomes despite missing values
Unlocking Time Series Potential with Synthetic Data
How Foundation Models Are Revolutionizing Time Series Analysis
Unlocking LLM Reasoning for Feature Generation
How advanced LLM reasoning techniques enhance machine learning capabilities
Optimizing HAR Across Heterogeneous Datasets
Applying LLM techniques to improve Human Activity Recognition
The Future of Data Science in Italy
Insights from ITADATA2024: Bridging Academia, Industry, and Public Administration
AI-Powered Medical Documentation in Pediatrics
Evaluating LLMs for Generating Quality Rehabilitation SOAP Notes
Consistent Hierarchical Classification
A mask-based approach for fair and consistent multi-level predictions
Smarter Cache Sharing for LLMs
Boosting inference efficiency through semantic similarity
Enhancing Clinical AI with Patient Experience
Using EHR data to make medical AI more accurate and reliable
Transforming Medical Phenotyping with LLMs
A new framework for evaluating AI-powered clinical data analysis
AI-Powered Thematic Analysis in Healthcare
Multi-Agent LLMs Revolutionizing Clinical Interview Analysis
AI Streamlining Clinical Documentation
LLMs Show Promise for Automated Pulmonary Embolism Data Extraction
Optimizing LLM Training for Medical Applications
Evaluating High-Performance Computing Frameworks for ECG Analysis
Intelligent Video Understanding
Advancing Real-Time Video Reasoning with Digital Twins
FaceBench: Evaluating Face Perception in AI Models
A hierarchical benchmark for assessing MLLMs' facial recognition capabilities
AI-Powered Cancer Classification
Ensemble approach combining small and large language models for automated tumor classification
LLMs as Anomaly Detection Partners
Using AI to refine time series anomaly detection across industries
The Rise of Agentic LLMs
How Large Language Models are Becoming Autonomous Agents
Simple Neural Networks Outperform Complex Models
Less complexity, better performance in time series forecasting
Augmenting EHR Disease Detection with AI
Combining LLM capabilities with human expertise for efficient medical diagnostics
AI-Powered Horizon Scanning in Healthcare
Accelerating innovation detection with SCANAR and AIDOC tools
Reinventing Healthcare Surveys with AI
Automated, Scalable Survey Collection Using LLM-Based Conversational Agents
Predicting Hospital Stays with AI
Using Liquid Time-Constant Networks for More Accurate Length of Stay Forecasts
Bridging Quantum and Geometric ML
A unified framework for enhanced medical and engineering applications
REANIMATOR: Breathing New Life into Test Collections
A framework for enriching retrieval test collections with extracted and synthetic data
Solving the Medical Vocabulary Gap
Enhancing EHR foundation models with flexible medical concept representation
AI-Powered ECG Analysis
Advancing cardiac diagnostics with minimal labeled data
Rethinking Privacy in AI Decision Systems
New privacy paradigms for RL and LLMs in sequential decisions
