Critical Care

The rise of artificial intelligence in respiratory primary care and pulmonology: a scoping review.

Artificial intelligence (AI) is rapidly advancing respiratory disease management, from diagnosis to population lung health. This scoping review synthesizes the most promising uses of AI in respiratory medicine, with a particular focus on pulmonologists and family physicians interested in lung health. In diagnostics, deep-learning systems streamline chest-imaging workflows by triaging radiographs, ...

A fuzzy ZE-number group decision-making framework using BWM and MABAC for risk assessment in medicinal plant extraction.

The extraction of bioactive compounds from medicinal plants is a crucial process in pharmaceutical and herbal medicine industries, yet it presents numerous challenges that can compromise quality, efficiency, and standardization. This study integrates Failure Mode and Effects Analysis (FMEA) with an advanced multi-criteria decision-making framework based on ZE-numbers, employing the ZE-based Best-W...

Lean mass loss in the intensive care unit and its restoration: A narrative review.

The preservation of lean mass (LM) and its restoration following catabolic loss represents a primary challenge for clinical nutrition in critically il...

From muscle to motion: GaIn nanoparticle-TPU core/shell mesh electrodes for intelligent prosthesis.

Electromyography (EMG) electrodes are critical for detecting and interpreting muscle activity, which is essential for operating prosthetic devices and...

Integrative multi-omics refines the molecular subtypes of thyroid cancers and enhances cancer-progression prediction: a retrospective cohort study.

BACKGROUND: Current molecular classification model for thyroid cancer (TC), which relies on BRAF-RAS score genes has limited efficacy in differentiati...

Comparison of respiratory-gated and breath‑hold accelerated T2-weighted sequences for liver MRI with deep learning reconstruction.

BACKGROUND: T2-weighted imaging (T2WI) of the liver suffers from prolonged scan times and respiratory motion artifacts. Deep learning (DL)-based recon...

Acute deep neck infection MRI: deep learning segmentation and clinical relevance of retropharyngeal edema volume.

OBJECTIVE: Retropharyngeal edema (RPE) on MRI in patients with acute neck infection is associated with disease severity. We explored the potential rol...

Cardiorespiratory Markers of Type 2 Diabetes: Machine Learning-Based Analysis.

BACKGROUND: The global prevalence of type 2 diabetes mellitus (T2DM) poses significant challenges due to its association with increased cardiovascular...

ChatGPT Health performance in a structured test of triage recommendations.

ChatGPT Health launched in January 2026 as OpenAI's consumer health tool, reaching millions of users. Here, we conducted a structured stress test of t...

A clinically interpretable prediction model for acute mortality in patients with pneumonia requiring mechanical ventilation.

The Evaluation of Transformer Models for the Detection of Adverse Drug Events: A Benchmark Study Using Dutch Free-Text Documents of Hospitalized Patients.

INTRODUCTION: Adverse drug events (ADEs) are a leading cause of preventable patient harm in hospitals. Because they are often recorded only in clinica...

Cerebrovascular 5D flow MRI.

BACKGROUND: 4D flow MRI facilitates quantification of cardiac phase-resolved blood velocity vector fields and has successfully been deployed to study ...

From machine learning to causal insight: a robust 12-gene signature to distinguish sepsis risk from systemic inflammatory response syndrome.

BACKGROUND: Sepsis, a life-threatening condition driven by a dysregulated host response, poses significant challenges for early diagnosis and early in...

Reimagining intensive care unit recovery: The Critical Illness Survivorship Programme for humanising post-intensive care unit care - A discussion paper.

BACKGROUND: Survivorship after critical illness is often characterised by fragmented recovery and lingering cognitive, psychological, and physical imp...

Multi-Score Reinforcement Learning for High-Tg Polyimide Design.

This study explores strategies to guide the generation of polyimides with high glass transition temperatures (Tg > 750 K) through reinforcement learni...

KD-SqueezeNet: an efficient deep learning strategy for the multi-task diagnosis of neonatal lung diseases.

BACKGROUND: The integration of deep learning in medical imaging has reached proficiency levels akin to expert clinicians, particularly in tasks requir...

Prediction of COVID-19 hospitalisation, ICU admission or death following ChAdOx1 vaccination using artificial intelligence: A clinical predictive model from the English RAVEN study.

OBJECTIVES: This study identifies predictors of severe COVID-19 following completion of two-dose primary series of the AZD1222 COVID-19 vaccine, emplo...

A hybrid CNN-spectral architecture for non-contact respiratory rate estimation using multi-region optical-flow analysis.

Respiratory rate (RR) is a key indicator for assessing health conditions, yet noncontact measurement remains challenging due to motion artifacts, ligh...

SCMO: a deep learning model integrating the single-cell resolution TME ecosystem and multi-omics for survival prediction in CRC patients.

BACKGROUND: Colorectal cancer (CRC) remains a leading cause of global cancer mortality, highlighting the need for precise survival prediction to guide...

Predicting surgical intensive care unit readmission with machine learning model: Bi-center training and validation.

BACKGROUND: Patients readmitted to the surgical intensive care unit (SICU) face a high risk of mortality and increased hospital costs. Identifying pat...