Papers ICU Mortality
“ICU Mortality” 태그가 달린 논문 45편 · 필터 해제
Towards end-to-end LLM-based censoring-aware survival analysis
Objective: Survival analysis is central to medical prediction, yet large language models (LLMs) are rarely used as end-to-end survival models because censoring prevents straightforward supervised fine-tuning. Here we pre…
ICU MortalityTraXion: Rethinking Pre-training Frameworks for Mobility and Beyond
Human mobility differs from text and from generic time series in three structural ways: visits are tuple-valued events whose meaning depends on the joint distribution over location, time, and activity; users carry persis…
Anomaly DetectionLink PredictionICU MortalityLearning temporal embeddings from electronic health records of chronic kidney disease patients
We investigate whether temporal embedding models trained on longitudinal electronic health records can learn clinically meaningful representations without compromising predictive performance, and how architectural choice…
Representation LearningICU MortalityImproving Fairness of Large Language Model-Based ICU Mortality Prediction via Case-Based Prompting
Accurately predicting mortality risk in intensive care unit (ICU) patients is essential for clinical decision-making. Although large language models (LLMs) show strong potential in structured medical prediction tasks, th…
ICU MortalityTransparent Early ICU Mortality Prediction with Clinical Transformer and Per-Case Modality Attribution
Early identification of intensive care patients at risk of in-hospital mortality enables timely intervention and efficient resource allocation. Despite high predictive performance, existing machine learning approaches la…
ICU MortalityClinStructor: AI-Powered Structuring of Unstructured Clinical Texts
Clinical notes contain valuable, context-rich information, but their unstructured format introduces several challenges, including unintended biases (e.g., gender or racial bias), and poor generalization across clinical s…
ICU MortalitySurvBench: A Standardised Preprocessing Pipeline for Multi-Modal Electronic Health Record Survival Analysis
Deep-learning survival models for electronic health record (EHR) data are hard to compare across papers because the upstream preprocessing step, which includes cohort definition, time discretisation, missingness handling…
ICU MortalityThink as a Doctor: An Interpretable AI Approach for ICU Mortality Prediction
Intensive Care Unit (ICU) mortality prediction, which estimates a patient's mortality status at discharge using EHRs collected early in an ICU admission, is vital in critical care. For this task, predictive accuracy alon…
Mortality PredictionICU MortalityChain-of-Influence: Tracing Interdependencies Across Time and Features in Clinical Predictive Modelings
Modeling clinical time-series data is hampered by the challenge of capturing latent, time-varying dependencies among features. State-of-the-art approaches often rely on black-box mechanisms or simple aggregation, failing…
ICU MortalitySimilarity-Based Self-Construct Graph Model for Predicting Patient Criticalness Using Graph Neural Networks and EHR Data
Accurately predicting the criticalness of ICU patients (such as in-ICU mortality risk) is vital for early intervention in critical care. However, conventional models often treat each patient in isolation and struggle to …
ICU MortalityAn MLI-Guided Framework for Subgroup-Aware Modeling in Electronic Health Records (AdaptHetero)
Machine learning interpretation (MLI) has primarily been leveraged to foster clinician trust and extract insights from electronic health records (EHRs), rather than to guide subgroup-specific, operationalizable modeling …
ICU MortalityBridging Data Gaps of Rare Conditions in ICU: A Multi-Disease Adaptation Approach for Clinical Prediction
Artificial Intelligence has revolutionised critical care for common conditions. Yet, rare conditions in the intensive care unit (ICU), including recognised rare diseases and low-prevalence conditions in the ICU, remain u…
Remaining Length of StayDomain AdaptationICU MortalityEarly Prediction of In-Hospital ICU Mortality Using Innovative First-Day Data: A Review
The intensive care unit (ICU) manages critically ill patients, many of whom face a high risk of mortality. Early and accurate prediction of in-hospital mortality within the first 24 hours of ICU admission is crucial for …
ICU AdmissionICU MortalityMachine Learning-Based Prediction of ICU Mortality in Sepsis-Associated Acute Kidney Injury Patients Using MIMIC-IV Database with Validation from eICU Database
Background: Sepsis-Associated Acute Kidney Injury (SA-AKI) leads to high mortality in intensive care. This study develops machine learning models using the Medical Information Mart for Intensive Care IV (MIMIC-IV) databa…
ICU MortalityMortality PredictionA Novel Multi-Task Teacher-Student Architecture with Self-Supervised Pretraining for 48-Hour Vasoactive-Inotropic Trend Analysis in Sepsis Mortality Prediction
Sepsis is a major cause of ICU mortality, where early recognition and effective interventions are essential for improving patient outcomes. However, the vasoactive-inotropic score (VIS) varies dynamically with a patient'…
ICU MortalityMortality PredictionZero Shot Health Trajectory Prediction Using Transformer
Integrating modern machine learning and clinical decision-making has great promise for mitigating healthcare's increasing cost and complexity. We introduce the Enhanced Transformer for Health Outcome Simulation (ETHOS), …
ICU AdmissionICU MortalityMortality PredictionReadmission PredictionAdvanced Predictive Modeling for Enhanced Mortality Prediction in ICU Stroke Patients Using Clinical Data
Background: Stroke is second-leading cause of disability and death among adults. Approximately 17 million people suffer from a stroke annually, with about 85% being ischemic strokes. Predicting mortality of ischemic stro…
feature selectionICU MortalityMortality PredictionSpecificityCluster trajectory of SOFA score in predicting mortality in sepsis
Objective: Sepsis is a life-threatening condition. Sequential Organ Failure Assessment (SOFA) score is commonly used to assess organ dysfunction and predict ICU mortality, but it is taken as a static measurement and fail…
Dynamic Time WarpingICU AdmissionICU MortalityICU Mortality Prediction Using Long Short-Term Memory Networks
Extensive bedside monitoring in Intensive Care Units (ICUs) has resulted in complex temporal data regarding patient physiology, which presents an upscale context for clinical data analysis. In the other hand, identifying…
ICU MortalityMortality PredictionTime SeriesAn empirical study of using radiology reports and images to improve ICU mortality prediction
Background: The predictive Intensive Care Unit (ICU) scoring system plays an important role in ICU management because it predicts important outcomes, especially mortality. Many scoring systems have been developed and use…
ICU MortalityManagementMortality PredictionSurvival Prediction