Critical Care

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

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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...

A Deep Learning–Based Automated Detection of Mucus Plugs in Chest CT

This study presents a novel two stage deep learning algorithm for automated detection of mucus plugs...

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...

Predictive Modeling of Heart Failure Readmissions

Federal programs to mitigate hospital readmission of patients with heart failure (HF) monetarily enc...

Predicting 28-Day Mortality in First-Time ICU Patients with Heart Failure and Hypertension Using LightGBM: A MIMIC-IV Study

Heart Failure (HF) and Hypertension (HTN) are common yet severe cardiovascular conditions, both of w...

Suitability of just-in-time adaptive intervention in post-COVID-19-related symptoms: A systematic scoping review

Patients with post-COVID-19-related symptoms require active and timely support in self-management. J...

PanEcho: Complete AI-enabled echocardiography interpretation with multi-task deep learning

Echocardiography is a cornerstone of cardiovascular care but relies on expert interpretation and man...

Understanding the Feasibility of Computer Vision in Diagnosing Respiratory Infections in Pediatric Emergency Rooms

Respiratory infections are a leading cause of pediatric emergency visits globally, requiring timely ...

A Novel Hybrid LSTM-DNN Model for Ventilator Pressure Prediction: Comparative Analysis of Data Splitting Strategies

In recent years, deep learning has significantly transformed ventilator pressure forecasting, which ...

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