Intensivists

Simulator development using natural language: clinician-led innovation through artificial intelligence.

BACKGROUND: Healthcare simulation training faces significant barriers due to the "clinician-developer gap," where educators lack programming expertise to create customized digital simulators. Natural Language-Driven Development (NLDD) is an emerging paradigm that enables clinicians to develop educational technology through conversational artificial intelligence interfaces. METHODS: We implemented ...

Machine Learning-Based Early Risk Stratification for Sepsis-Related Troponin-Defined Myocardial Injury Using Routine Metabolic Indicators.

BACKGROUND: Early recognition of sepsis-related myocardial injury during sepsis remains difficult, partly because harmonized echocardiographic phenotyping is often unavailable in retrospective critical-care datasets. Routine metabolic indicators, including the triglyceride-glucose (TyG) index and the triglyceride-to-HDL cholesterol (TG/HDL) ratio, may support early risk stratification, but their v...

Leashing heterogeneous sepsis with phenotype-informed decision support modeling.

Non-invasive arterial blood pressure waveform generation in critically ill patients: A sensor-based deep learning approach.

Continuous monitoring of Arterial Blood Pressure (ABP) in critically ill patients requires invasive arterial catheterization, which carries risks of t...

An interpretable machine learning model for early prediction of ESBL-producing bacteraemia in the emergency department.

Empirical antibiotic therapy in the emergency department (ED) is often initiated before susceptibility results are available, risking treatment failur...

Enhancing mortality prediction in septic ICU patients with malignancies through ensemble machine learning: a retrospective cohort study.

Sepsis remains a leading cause of mortality in the intensive care unit (ICU), and patients with underlying malignancies are disproportionately affecte...

Fairness in multimodal machine learning applications in clinical decision support: a systematic review.

Multimodal AI models are increasingly used in clinical decision support systems, but fairness appears to be rarely measured. In this systematic review...

Association Between the Hemoglobin-to-Red Blood Cell Distribution Width Ratio and Perioperative Mortality Risk in Myasthenia Gravis Patients with Sepsis: A Retrospective Cohort Study.

BackgroundThis study aims to explore the association between the Hemoglobin/Red Cell Distribution Width Ratio (HRR) and perioperative mortality in mya...

Data-driven subtypes of postoperative delirium in surgical ICU patients: a secondary analysis of a prospective cohort study.

BACKGROUND: Postoperative delirium (POD) is a heterogeneous syndrome associated with adverse outcomes. Traditional classifications may obscure underly...

Explainable early prediction of short-term severe deterioration in gallstone-related biliary disease using MIMIC-IV, eICU, and local real-world data.

BACKGROUND: Patients with gallstone-related biliary disease may deteriorate rapidly before definitive source control. This study aimed to develop an i...

Integrating untargeted metabolomics and machine learning to reveal an aberration of sphingolipid metabolism in cardiometabolic HFpEF.

BACKGROUND: Cardiometabolic heart failure with preserved ejection fraction (HFpEF) is a high-risk phenotype primarily driven by metabolic syndrome, wi...

Structure-aware fatigue modeling in foot deformities: A digital health framework for tissue-specific running injury risk prediction using multi-modal data.

Hallux Valgus (HV) is a common deformity in runners that reflects altered foot morphology and thereby redistributes mechanical loads along the lower l...

A 2004-2025 Bibliometric Study of Genetic Variation and Multiomics Biomarkers in Sepsis Based on 940 Publications.

Sepsis is a highly heterogeneous syndrome, and conventional clinical indicators and single biomarkers often fail to capture its biological complexity ...

Metal-organic frameworks (MOFs) for nonlinear optical properties: design principles, DFT insights, and future directions for photonic applications.

Metal-organic frameworks (MOFs) have emerged as a uniquely versatile platform for nonlinear optical (NLO) applications, combining the large hyperpolar...

Correction: Enterocutaneous Fistula-Associated Sepsis and Mortality: Development and Validation of a Multimodal Artificial Intelligence Prediction Model.

[This corrects the article DOI: 10.2196/79985.].

A blood gas parameter-based assessment model for predicting poor prognosis in sepsis: A retrospective analysis of the MIMIC-IV and eICU-CRD.

BACKGROUND: Blood gas parameters are associated with sepsis prognosis. This study aimed to develop an assessment model based on blood gas parameters f...

Development and validation of a novel multimodal deep neural network model based on CBC digit parameters and scattergrams for rapid hematolymphoid malignancy classification: a multicenter cohort study.

BACKGROUND: Rapid screening of hematolymphoid malignancies (HMs) by complete blood cell count (CBC) is crucial for choosing the next appropriate worku...

Reporting follow-up budgets for diagnostic and predictive AI.

OBJECTIVE: To argue that diagnostic and predictive AI should be evaluated by both classification performance and the downstream work their outputs cre...

Impact of an Artificial Intelligence-Powered Clinical Decision Support System for Acute Kidney Injury Prevention in the Intensive Care Unit: Single-Center Uncontrolled Before-and-After Implementation Study.

BACKGROUND: Acute kidney injury (AKI) is a frequent and serious complication among hospitalized patients, particularly in critical care settings, wher...

The hidden infectious disease-related sepsis risk of wildfire-specific PM2.5.

Wildfire smoke is a major source of fine particulate matter (PM2.5) and may increase vulnerability to severe infectious outcomes such as sepsis, a con...