Critical Care

Latest AI and machine learning research in critical care for healthcare professionals.

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Multi-resolution vision transformer model for skin cancer subtype classification using histopathology slides

Digital pathology has significantly advanced cancer diagnosis by enabling high-resolution visualisat...

NutriSighT: Interpretable Transformer Model for Dynamic Prediction of Hypocaloric Enteral Nutrition in Mechanically Ventilated Patients

Achieving adequate enteral nutrition among mechanically ventilated patients is challenging, yet crit...

A deep learning model for clinical outcome prediction using longitudinal inpatient electronic health records

Recent advances in deep learning show significant potential in analyzing continuous monitoring elect...

Development and Validation of Machine Learning Models for Adverse Events after Cardiac Surgery

Early recognition of adverse events after cardiac surgery is vital for treatment. However, the widel...

Generative AI Mitigates Representation Bias and Improves Model Fairness Through Synthetic Health Data

Representation bias in health data can lead to unfair decisions and compromise the generalisability ...

Machine Learning Models for Dynamic Assessment of Extubation Readiness in Pediatric Critical Care

Determining the optimal timing for extubation in critically ill children remains challenging, with p...

Integrating Nowcasts into an Ensemble of Data-Driven Forecasting Models for SARI Hospitalizations in Germany

Predictive epidemic modeling can enhance situational awareness during emerging and seasonal outbreak...

Predicting mortality in critically ill patients with hypertension using machine learning and deep learning models

Accurate prediction of mortality in critically ill patients with hypertension admitted to the Intens...

Development of Interactive Nomograms for Predicting Short-Term Survival in ICU Patients with Aplastic Anemia

Aplastic anemia is a severe hematologic disorder marked by pancytopenia and bone marrow failure. ICU...

The impact of evaluation strategy on sepsis prediction model performance metrics in intensive care data

The prediction of the onset of sepsis, a life-threatening condition resulting from a dysregulated re...

InfEHR: Resolving Clinical Uncertainty through Deep Geometric Learning on Electronic Health Records

Electronic health records (EHRs) contain multimodal data that can inform diagnostic and prognostic c...

Plasma proteomics for novel biomarker discovery in childhood tuberculosis

Failure to rapidly diagnose tuberculosis disease (TB) and initiate treatment is a driving factor of ...

Quality of Human Expert vs. Large Language Model Generated Multiple Choice Questions in the Field of Mechanical Ventilation

Mechanical ventilation (MV) is a critical competency in critical care training, yet standardized met...

Predicting in-hospital indicators from wearable-derived signals for cardiovascular and respiratory disease monitoring: an in silico study

Cardiovascular and respiratory diseases (CVRD) are the leading causes of death worldwide. The constr...

Open-source computational pipeline automatically flags instances of acute respiratory distress syndrome from electronic health records

Physicians, particularly intensivists, face information overload and decision fatigue, underscoring ...

Prediction of the infecting organism in peritoneal dialysis patients with acute peritonitis using interpretable Tsetlin Machines

The analysis of complex biomedical datasets is becoming central to understanding disease mechanisms,...

Profile of deaths mentioning ischemic and hemorrhagic stroke in Brazil: a population-based machine learning analysis

Brazil has the highest stroke rates in Latin America. The aim of this study was to investigate the p...

Development and Prospective Implementation of a Large Language Model based System for Early Sepsis Prediction

Sepsis is a dysregulated host response to infection with high mortality and morbidity. Early detecti...

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