Time Series Representation Learning 📈
Time Series Representation Learning 📈
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Medical Intelligent Digital Twin
Integrating medical knowledge with multimodal AI
Learning robust temporal representations for dynamic patient trajectories
Simulating organ-specific medical digital twins
Predictive clustering-based time series representation learning
Variational inference and predictive clusteirng based representation learning
Soft cluster assignment and center mechanism for interpretable representation
Representation based intutitve and actionable monitoring of pathophysiology for critical illness
Causality-aware embedding of irregular time series
Graph-based embedding of missing information
Learning balanced representation for causal relationship modeling
Disease detection and counterfactual outcome simulation for treatment effect evaluation
Contrastive learning for EHR
Supervised contrastive learning
Deep representation learning for EHR
Prognostic monitoring system for shock in ICU patients
Language Models for EHR 💬
Language Models for EHR 💬
Agentic LLM for clinical question answering in the ICU
Tool-augmented action planning for causal simulation
Trajectory-based fine-tuning and RLHF optimization
Developing an agentic LLM for clinical QA
PEFT-based test-time adaptation of LLMs for EHRs
LoRA-based TTA for multi-site EHR robustness
LLM-based unified embedding module for diverse EHR features
Cross-modal alignment of irregular time series and text
LLM-based representation learning for irregular time series
Inference of missing vital sign values using a pre-trained LLM
Lab result embedding based on temporal similarity between observed time and overall time
Deriving feature importance through variable self-attention
Self-supervised foundation model for ICU
Self-supervised foundation model trained on irregular, event-based ICU timep series data
EHR sequence representation via attribute-specific embedding mechanism
Captures both local and global information via dual-attention based Transformer
EHR Multimodal Learning 📊🧬📄
EHR Multimodal Learning 📊🧬📄
Multimodal fusion of EHR
Robust representation learning from incomplete multimodal clinical data
Cross-modal temporal alignment
Online risk monitoring framework for pulmonary diseases
Wearable IoT-enabled health monitoring system
Deep representation learning for EHR
Time series clustering of cardiac rehabilitation recovery pattern
Wearable monitoring device
Reinforcement Learning 🖥️
Reinforcement Learning 🖥️
Frictional off-policy RL
Physical anaology for representing extrapolation error
Expanded and improved constraint with replay buffer
Contrastive variational autoencoder using orthogonal action space
Safe and reasonable medical AI
Clinician-informed RL for shock treatment
Multi-agent RL framework for enhancing clinical stability
Treatment decision system integrating clinical reasoning
Medical dead-ends for safe RL
Safe reinforcement learning
Multi-agent deep reinforcement learning
Identifying high risk states and management of nephrotoxic drugs
Multimodal RL for embedding networks
Deep reinforcement learning
Multimodal data integration
Medication recommendation for Parkinsons' disease
Time Series Anomaly Detection 🔎
Time Series Anomaly Detection 🔎
Sequential anomaly detection for clinical deterioration
Time series anomaly detection
Early warning system for clinical deterioration
Detection of unexpected ICU admissions from ED
🏥 Medical Partners 🧑🤝🧑
🏥 Medical Partners 🧑🤝🧑
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