Hospital-Based Medicine

Intensivists

Latest AI and machine learning research in intensivists for healthcare professionals.

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Showing 358-378 of 4,970 articles
Development and validation of a transformer model-based early warning score for real-time prediction of adverse outcomes in the emergency department.

This study aimed to develop and validate a transformer-based early warning score (TEWS) system for p...

Jul 2025 40593229
Machine learning model and hemoglobin to red cell distribution width ratio evaluates all-cause mortality in pulmonary embolism.

The ratio of hemoglobin (Hb) to red blood cell distribution width (RDW), known as HRR, functions as ...

Jul 2025 40594595
Self-Powered Multimodal Tactile Sensing Enabled by Hybrid Triboelectric and Magnetoelastic Mechanisms.

Object property perception, as a core component of tactile sensing technology, faces severe challeng...

Jul 2025 40607079
Patient radiation safety in the intensive care unit.

The aim of this commentary review was to summarize the main research evidences on radiation exposure...

Jul 2025 40591456
Enhancing anomaly detection and prevention in Internet of Things (IoT) using deep neural networks and blockchain based cyber security.

The rapid adoption of Internet of Things (IoT) devices has significantly increased cybersecurity ris...

Jul 2025 40593899
A hybrid prediction and multi-objective optimization framework for limestone calcined clay cement concrete mixture design.

Limestone calcined clay cement (LC) is a promising low-carbon construction material in terms of its ...

Jul 2025 40594099
[Early warning scores: a rapid umbrella review].

BACKGROUND: Early warning scores (EWS) are used for monitoring and evaluating vital signs in hospita...

Jun 2025 40576804
Renal Dysfunction Across the Spectrum of Cardiogenic Shock: Mechanisms, Clinical Implications, and Therapeutic Strategies.

PURPOSE OF REVIEW: This review aims to elucidate the complex interplay between cardiogenic shock (CS...

Jun 2025 40560292
Comprehensive analysis and experimental validation of BST1 as a novel diagnostic biomarker for pediatric sepsis using multiple machine learning algorithms.

Bone marrow stromal cell antigen-1 (BST1) expression is elevated in a variety of human diseases, but...

Jun 2025 40555937
High-precision deformation monitoring and intelligent early warning for wellbore based on BDS/GNSS.

To address the complex deformation of wellbores influenced by surrounding coal mining operations, th...

Jun 2025 40549791
Disease entity impacts muscle wasting in the ICU with COVID-19 patients losing muscle nearly twice as fast.

Muscle loss in critically ill patients, particularly during prolonged ICU stays, poses significant c...

Jun 2025 40542071
Prediction of Sepsis after Endourologic Kidney Stone Surgery: A Machine Learning Approach.

Sepsis secondary to urinary tract infection after kidney stone surgery is associated with considera...

Jun 2025 40533084
Traumatic brain injury management in the intensive care unit: standard of care and knowledge gaps.

Despite advances in the management of traumatic brain injury (TBI) in the intensive care unit (ICU),...

Jun 2025 40522481
Harnessing AI in critical care: opportunities, challenges and key steps for success.

BACKGROUND: The integration of artificial intelligence (AI) into critical care offers significant po...

Jun 2025 40518257
Exploring the molecular mechanisms of lactylation-related biological functions and immune regulation in sepsis-associated acute kidney injury.

Lactylation, a novel post-translational modification, has been implicated in various pathophysiologi...

Jun 2025 40504273
Predicting carbapenem-resistant Pseudomonas aeruginosa infection risk using XGBoost model and explainability.

The prevalence and spread of carbapenem-resistant Pseudomonas aeruginosa (CRPA) is a global public h...

Jun 2025 40473759
Machine learning models for predicting severe acute kidney injury in patients with sepsis-induced myocardial injury.

Severe acute kidney injury (sAKI) is a prevalent and serious complication among patients with sepsis...

Jun 2025 40467843
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