Critical Care

Building a Quantitative Telemedicine Platform for Myasthenia Gravis: Augmenting the Physical Examination.

Myasthenia gravis (MG), a fluctuating autoimmune neuromuscular disease, presents unique challenges for remote assessment due to its reliance on detailed physical examination. To address this, we developed a quantitative telemedicine platform that augments traditional neurological assessments using computer vision, signal processing, and augmented intelligence. In response to the COVID-19 pandemic ...

Learning curve for fenestrated-branched endovascular aortic repair using machine learning: A prospective national multicenter registry study.

OBJECTIVE: Fenestrated-branched endovascular aortic repair (F-BEVAR) is a complex procedure that requires significant experience and advanced technical proficiency. This study leverages machine learning methods to analyze the learning curve for F-BEVAR in the treatment of complex abdominal and thoracoabdominal aortic aneurysms (TAAAs). METHODS: Patients undergoing three- and four-vessel F-BEVAR fo...

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 substantial chronic comorbidities recover more slowl...

Artificial intelligence in nephrology: predicting CKD progression and personalizing treatment.

Chronic kidney disease (CKD) represents a major and expanding global health challenge, with prevalence rising due to aging populations, diabetes, hype...

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 approach to identify individuals at risk for heart failur...

Responsible Use of Artificial Intelligence to Improve Kidney Care: A Statement from the American Society of Nephrology.

Artificial intelligence (AI) is rapidly transforming the delivery of kidney care through predictive analytics, machine learning, deep learning, and ge...

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 reasoning for sepsis surveillance. We provide prelim...

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-making and emergency management skills. Simulation-ba...

Multi-teacher knowledge distillation framework for lightweight anomaly detection.

Anomaly detection is essential in various domains, where identifying rare and irregular samples is critical for system safety and security. This probl...

Takotsubo cardiomyopathy: Advances in pathophysiology, diagnostic biomarkers, genetic insights, multisystemic involvement, treatment updates & multidisciplinary interventions.

BACKGROUND: Takotsubo cardiomyopathy (TTC) is an acute, reversible cardiac syndrome triggered by physical or emotional stress, involving complex multi...

Machine Learning Based Prediction of 28-Day Mortality in ECMO Patients: A Pilot Study Using MIMIC-IV Database.

BackgroundExtracorporeal membrane oxygenation (ECMO) is a critical life-sustaining intervention for patients with severe cardiac or respiratory failur...

Artificial intelligence for arterial blood gas interpretation.

Arterial blood gas (ABG) analysis is a fundamental diagnostic tool in clinical medicine, offering critical insights into a patient's respiratory and m...

Letter to the Editor: "A risk-adjusted length of stay to evaluate severe community-acquired pneumonia (sCAP) outcomes: A machine learning analysis of 16,985 ICU admissions".

Perioperative Extracorporeal Membrane Oxygenation Use in Lung Transplantation: Analysis of Outcomes and Future Directions.

Extracorporeal membrane oxygenation (ECMO) has emerged as a critical intervention in the management of patients with end-stage lung disease undergoing...

"PD-PREDICT": A Machine Learning Model for Patient Survival in Peritoneal Dialysis.

Accurate survival prediction in peritoneal dialysis (PD) patients is essential for personalized treatment planning and shared decision-making. We deve...

Multimodal deep learning for acute myocardial infarction detection from 12-lead electrocardiogram: a multi-centre study with cross-hospital validation.

AIMS: Acute myocardial infarction (AMI) remains a leading global cause of mortality, where timely diagnosis is critical to enable early intervention. ...

Artificial Intelligence Models for Diagnosing Pulpitis in Adults Using a Modified Wolters Classification: A Diagnostic Accuracy Study.

AIM: To evaluate the performance of an artificial intelligence (AI) system in diagnosing pulp conditions in adult patients, using a modified Wolters d...

Robotic thoracic surgery: what is different in anesthesia?

PURPOSE OF REVIEW: Robotic-assisted thoracic surgery (RATS) has emerged as a transformative approach in thoracic surgery, enabling enhanced precision ...