Intensivists

AI-Assisted Dialysis Decision-Making: Assessing Agreement Between ChatGPT and Nephrologist in Initial Dialysis Indication and Prescription in Emergency and ICU Settings.

BACKGROUND Artificial intelligence (AI) is increasingly explored as a clinical decision-support tool in nephrology; however, its real-world applicability for dialysis decision-making in emergency and intensive care unit (ICU) settings remains insufficiently studied. Hemodialysis initiation and prescription are complex, time-sensitive, and dynamic processes that require expert clinical judgment. MA...

Magnetically controlled capsule endoscopy: Innovations, standardized practice, and emerging clinical roles.

Capsule endoscopy has transformed small bowel evaluation but remains limited for gastric examination because of passive, peristalsis dependent movement. Magnetically controlled capsule endoscopy (MCE) addresses this limitation by enabling real time external steering of the capsule, allowing systematic visualization of the spacious gastric cavity without sedation or intubation. Since the first huma...

NQO1-Mediated Anoikis Resistance and Immune Evasion Define a High-Risk Multi-Omic Subtype for Precision Management of T1 High-Grade Bladder Cancer.

T1 high-grade (T1HG) bladder cancer represents an aggressive subset of non-muscle-invasive bladder cancer (NMIBC) with frequent Bacillus Calmette-Guér...

Development and external validation of a machine learning model for predicting chronic critical illness in ICU patients with acute pancreatitis.

BACKGROUND: To develop and validate a machine learning (ML) model to assess the risk of chronic critical illness (CCI) in intensive care unit (ICU) pa...

A Histone Deacetylase Activity Model for the Discovery and Validation of Sepsis Biomarkers.

INTRODUCTION: Histone deacetylases (HDACs) play critical roles in immune regulation and inflammatory responses in sepsis. This study identified HDAC-r...

Predicting public Intensive care unit mortality and hospitalization using Data: An evaluation of Brazil's Largest COVID-19 epidemiological dataset.

OBJECTIVES: To assess the SRAG dataset's potential for modeling COVID-19 mortality and LOS-ICU, identify key data gaps, and support the development of...

MoSA-Det: motion state adaptive object detection for sports videos.

Object detection in sports videos serves as a fundamental task for applications such as intelligent broadcasting, tactical analysis, and athlete track...

Artificial intelligence-driven cluster analysis for identifying clinical phenotypes in suspected sepsis patients in the emergency department.

Building your future ICU in Asia Pacific: A structured regional priority-mapping summit report from the Asia Pacific Critical Care Societies Summit 2025.

OBJECTIVE: To summarise the proceedings of the third Asia Pacific Critical Care Societies Summit and identify regionally aligned priorities for the "F...

Exploratory prediction model for deep vein thrombosis in intensive care patients after anticoagulation therapy: An observational study.

BACKGROUND: Despite low-molecular-weight heparin (LMWH) prophylaxis, the incidence of deep vein thrombosis (DVT) remains high in intensive care unit (...

Fuzzy-logic-driven predictions of multi-tissue ingrowth for rapid screening of mechanically instructive tissue-engineering scaffolds.

High retear rates in surgical intervention of interfacial/transitional tissues (bone-tendon, bone-ligament) drive a need to design tissue engineering ...

SELFormer-guided discovery of xanthohumol and cirsilineol as multi-target natural therapeutics for type 2 diabetes: computational prediction and experimental validation.

Type 2 diabetes mellitus (T2DM) requires multi-target therapeutic approaches addressing both insulin resistance and insulin secretion deficits. Althou...

Predicting one-year mortality risk in ICU patients with ischemic stroke using multi-algorithm machine learning and a nomogram.

Introduction: Ischemic stroke is a leading cause of mortality, and patients requiring intensive care unit (ICU) admission carry a guarded prognosis. W...

Transforming a fragile protein helix into an ultrastable scaffold via a hierarchical AI and chemistry framework.

The rational design of proteins that maintain structural integrity under concurrent thermal, mechanical, and chemical stress remains a challenge in mo...

Deep learning improves image quality in motion-robust and sedation-free pediatric brain MRI.

OBJECTIVES: Motion and limited compliance compromise diagnostic MR image quality, particularly in pediatric patients who frequently require sedation. ...

A machine learning model for post-operative sepsis prediction in acute surgical patients: a multi-centre, prospective study.

Performance of Large Language Models vs Conventional Machine Learning for Predicting Clinical Outcomes With Limited Data: Comparative Study.

BACKGROUND: Machine learning (ML) can be used to predict clinical outcomes. Training predictive models typically requires data for hundreds or thousan...

A Machine Learning-Based Model for Individualized Prediction of Vancomycin Concentration-Time Curves in ICU Patients.

Therapeutic drug monitoring is essential for ensuring the efficacy and safety of vancomycin therapy in critically ill patients. This study aimed to de...

DILIConsult: A Multi-Agent Large Language Model Framework for Evaluating Drug-Induced Liver Injury in ICU Settings.

BACKGROUND: Large language models (LLMs) can support clinical decision-making by parsing databases and extracting relevant information. However, evalu...

Predicting ventilation from single breathing phase non-contrast CT using Swin Transformers.

BACKGROUND: Pulmonary ventilation imaging enables functional avoidance radiotherapy treatment plans by quantifying regional lung function. However, cu...