Critical Care

Functional-based multi-omics early prediction of radiation pneumonitis in NSCLC using AI-generated perfusion and ventilation from planning CT.

ObjectiveThis study aims to develop a functional-based multi-omics model for early prediction of rad...

[Care for uncontrolled asthma in Germany - with focus on Magdeburg and Mannheim regions].

Description of treatment and prescription patterns among asthma patients in the regions of Magdeburg...

Bayesian networks for predicting clinical outcomes in COVID-19 patients: A retrospective study in a resource-limited setting.

BACKGROUND: The COVID-19 pandemic has highlighted the critical need for robust, interpretable predic...

Systematic review of Artificial Intelligence-based methods for glycemic control and risk prediction in intensive care units.

BACKGROUND: Achieving safe glycemic targets in intensive care remains difficult due to rapidly chang...

Infrared thermography in the detection of arthritis: a systematic review of diagnostic performance compared with joint ultrasound.

Early detection of arthritis in autoimmune rheumatic diseases (ARDs) is critical to prevent irrevers...

Detecting multimorbidity patterns in Alzheimer's disease using unsupervised machine learning: A nationwide emergency department study (2007-2022).

BackgroundAlzheimer's disease (AD) patients frequently present to emergency departments (EDs) with c...

[Annual progress in critical care of pulmonary medicine 2025].

This review systematically summarizes the annual research advances in the field of critical care of ...

Modern machine learning techniques used in prediction of sepsis and bloodstream infection in burn patients: A systematic review.

INTRODUCTION: Burn patients are a group highly prone to sepsis and bloodstream infections (BSIs) due...

Community medical centers struggle to produce well-calibrated clinical prediction models: Data augmentation can help.

OBJECTIVE: Machine learning models (ML) often require localization to perform optimally in local pop...

Deep learning-based 4D robust optimization of intensity-modulated proton therapy for lung cancer radiotherapy.

Intensity-modulated proton therapy (IMPT) provides steep dose gradients but is vulnerable to range u...

A machine learning-based model to predict multi-time-point prognosis for acute-on-chronic hepatitis B liver failure.

Our prognostic model and mobile application enable multi-time-point prognostic evaluation for patien...

Identifying and timing patient outcomes in clinician notes using large language models.

BACKGROUND: Key challenges in leveraging unstructured clinician notes for predictive models include ...

Resveratrol ameliorates sepsis-induced immune dysfunction by targeting GADD45A to maintain hematopoietic stem cell homeostasis: A predictive study integrating ensemble machine learning, single-cell transcriptomics, and molecular dynamics simulation.

OBJECTIVE: To investigate the potential pharmacological mechanisms of resveratrol (RES) in ameliorat...

Machine learning-based prognostic analysis of patients with status epilepticus in the neurological intensive care unit.

OBJECTIVE: This study aimed to develop and validate machine learning (ML) models for predicting the ...

Precise oxygen therapy to emphysema patients by fuzzy-based gain tuning control of set-point regulated MRAC.

Emphysema, a primary component of chronic obstructive pulmonary disease (COPD), causes progressive d...

Preoperative Risk Score for Mortality Within 3 Years of Elective Aortobifemoral Artery Bypass.

BACKGROUND: The purpose of this study was to create a risk score for mortality within 3 years of ele...

Machine learning prediction model for delirium after heart valve replacement with cardiopulmonary bypass: A large-scale cohort study.

OBJECTIVE: Postoperative delirium (POD) is a common and severe complication following heart valve re...

Respiratory sound analysis for ICU clinical decision support: deep learning-based classification of normal and abnormal sounds using real ICU data.

Integrative multi-omics and machine learning identify mitochondrial biomarkers for pathogen-specific sepsis stratification and translational prioritization.

BACKGROUND: Sepsis is a leading cause of critical illness and mortality, yet substantial heterogenei...

Early Prediction of Standing at Discharge in Moderate-to-Severe TBI: A Clinical Machine Learning Model Integrating Modifiable and Nonmodifiable Factors.

OBJECTIVE: To develop and internally validate a machine learning model to predict favorable standing...

Screening of Respiratory Toxicity of Environmental Compounds Based on Multimodal Feature Fusion Model.

The respiratory system constitutes the primary interface between the human body and the external env...