Intensivists

Chemically-informed active learning enables data-efficient multi-objective optimization of self-healing polyurethanes.

Self-healing polyurethanes (PUs) exhibit an inherent trade-off between mechanical strength and self-...

Widely targeted metabolomics and machine learning identify succinate as a key metabolite in sepsis-associated encephalopathy.

Sepsis-associated encephalopathy (SAE) is a common and serious complication of sepsis that leads to ...

Progress in constitutive modeling of arterial wall tissue mechanics: from theoretical frameworks to clinical application.

Cardiovascular disease (CVD) is a leading cause of mortality worldwide, and the mechanical behavior ...

Multi-view deep learning for mandibular landmark localization.

OBJECTIVES: Accurate localization of anatomical landmarks on the mandible is crucial for maxillofaci...

Development and multicenter validation of a machine learning model for postoperative sepsis risk in critically Ill traumatic spinal injury patients.

OBJECTIVE: To develop and validate a machine learning model for postoperative sepsis in critically i...

Pharmacoepidemiologic characterization of cannabis use and symptomatology in rheumatology using natural language processing of electronic health record clinic notes.

Up to 70% of patients with autoimmune rheumatic diseases (ARDs), including rheumatoid arthritis, pso...

Artificial Intelligence and Machine Learning in Health Care: Current Capabilities, Emerging Potential, and Future Directions.

This article reviews how artificial intelligence and machine learning are reshaping health care. Aft...

Molecular crystal memristor-based edge AI platform for energy-efficient and real-time smart grid inspection.

Vast power grid infrastructure generates enormous volumes of inspection data from smart meters, unma...

Machine Learning-Based Prediction of Postoperative Vasoplegia After Cardiac Surgery.

OBJECTIVE: To develop and internally validate a machine-learning model for the early prediction of p...

Pressure injury surveillance in the intensive care unit: Development, validation, and clinical application of a natural language processing algorithm.

INTRODUCTION: Pressure injuries (PIs) are one of the most common hospital-acquired complications in ...

Development and validation of deep continual learning model to sequentially learn multiple clinical prediction tasks for ICU patients.

BACKGROUND: ICU patients often suffer from critical and complex condition, and multiple potential ri...

Artificial intelligence-guided nutritional therapy in the ICU.

PURPOSE OF REVIEW: Critical care nutrition remains a high-stakes and error-prone domain, particularl...

Development and validation of a machine learning model to predict 30-day mortality in ischemic stroke patients with consciousness impairment: Insights from MIMIC-IV database and multicenter ICU data in China.

BACKGROUND: Patients with ischemic stroke complicated by consciousness disorders remain associated w...

Authors reply: "How do experts classify sepsis cases for sepsis surveillance? Lessons learned from a Behavioural Artificial Intelligence Technology (BAIT) approach".

The Ideal Human Care in Green ICU: An integrated AI framework for future ICU care - Letter on Arabfard et al.

An explainable machine learning model for comorbidity risk stratification in patients with fractures admitted to the intensive care unit: a multicenter study.

BACKGROUND: Among traumatic-fracture patients admitted to intensive care units (ICUs), those with su...

Predicting Heart Failure From 12-Lead ECGs Using AI: A HeartShare/AMP-HF Pooled Cohort Analysis.

BACKGROUND: Artificial intelligence applied to electrocardiograms (ECG-AI) offers a scalable approac...

Letter to the editor: "How do experts classify sepsis cases for sepsis surveillance? Lessons learned from a behavioural artificial intelligence technology (BAIT) approach".

Behavioural Artificial Intelligence Technology (BAIT) has recently been proposed to codify expert re...

Toward transparent clinical decision support in the ICU: A multi-window, model-agnostic explainability approach for 72-h mortality prediction using the eICU collaborative research database.

OBJECTIVE: This study has two main objectives: (1) to develop a multi-model framework for predicting...

LLM-based pedagogical agent for ICU simulation instructor training: A quasi-experimental study.

BACKGROUND: Intensive Care Unit (ICU) nursing is demanding, requiring advanced clinical decision-mak...

Identification and Validation of Key Genes Related to Arginine Methylation Modification in Sepsis Using Transcriptome Combined with Mendelian Randomization Analysis.

BACKGROUND: Patients with sepsis often exhibit a decrease in lymphatic numbers, which can be facilit...