Hospital-Based Medicine

Enhancing Ophthalmic Anesthesia Optimization with Predictive Embedding Models.

Ophthalmic anesthesia the crucial factors in success and safety of ophthalmic surgery, which involve...

Clinical subtypes identification and feature recognition of sepsis leukocyte trajectories based on machine learning.

Sepsis is a highly variable condition, and tracking leukocyte patterns may offer insights for tailor...

Bridging Data Gaps in Emergency Care: The NIGHTINGALE Project and the Future of AI in Mass Casualty Management.

In the context of mass casualty incident (MCI) management, artificial intelligence (AI) represents a...

Comprehensive analyses: Using machine learning models for mortality prediction in the intensive care unit of internal medicine.

Mortality prediction in the intensive care unit (ICU) is essential in patient management. Emerging m...

Improving Phenotyping of Patients With Immune-Mediated Inflammatory Diseases Through Automated Processing of Discharge Summaries: Multicenter Cohort Study.

BACKGROUND: Valuable insights gathered by clinicians during their inquiries and documented in textua...

Gender Disparities in Artificial Intelligence-Generated Images of Hospital Leadership in the United States.

OBJECTIVE: To evaluate demographic representation in artificial intelligence (AI)-generated images o...

Transformer-based deep learning ensemble framework predicts autism spectrum disorder using health administrative and birth registry data.

Early diagnosis and access to resources, support and therapy are critical for improving long-term ou...

Evaluation of machine learning methods for prediction of heart failure mortality and readmission: meta-analysis.

BACKGROUND: Heart failure (HF) impacts nearly 6 million individuals in the U.S., with a projected 46...

Predicting hospital admissions, ICU utilization, and prolonged length of stay among febrile pediatric emergency department patients using incomplete and imbalanced electronic health record (EHR) data strategies.

OBJECTIVE: Determine the efficacy of commonly used approaches to handling missing and/or imbalanced ...

Comment on "Machine learning risk-prediction model for in-hospital mortality in Takotsubo cardiomyopathy".

Clinical implementation of AI-based screening for risk for opioid use disorder in hospitalized adults.

Adults with opioid use disorder (OUD) are at increased risk for opioid-related complications and rep...

Real-time surveillance system for patient deterioration: a pragmatic cluster-randomized controlled trial.

The COmmunicating Narrative Concerns Entered by RNs (CONCERN) early warning system (EWS) uses real-t...

Preoperative Factors Associated With In-Hospital Major Bleeding After Percutaneous Coronary Intervention: A Systematic Review.

BACKGROUND: Preoperative risk assessment of bleeding after percutaneous coronary intervention (PCI) ...

Enhanced prediction of ventilator-associated pneumonia in patients with traumatic brain injury using advanced machine learning techniques.

Ventilator-associated pneumonia significantly increases morbidity, mortality, and healthcare costs a...

Beyond the Mirror: Body Dysmorphic Disorder and Emerging Dysmorphias in Aesthetic Surgery.

Driven by social media and artificial intelligence technologies, new dysmorphias increase pressures ...

Gender Differences in Predicting Metabolic Syndrome Among Hospital Employees Using Machine Learning Models: A Population-Based Study.

BACKGROUND: Metabolic syndrome (MetS) is a complex condition that captures several markers of dysreg...

Adoption of Large Language Model AI Tools in Everyday Tasks: Multisite Cross-Sectional Qualitative Study of Chinese Hospital Administrators.

BACKGROUND: Large language model (LLM) artificial intelligence (AI) tools have the potential to stre...

Benchmarking of Large Language Models for the Dental Admission Test.

Large language models (LLMs) have shown promise in educational applications, but their performance ...

Predicting Clinical Outcomes at the Toronto General Hospital Transitional Pain Service via the Manage My Pain App: Machine Learning Approach.

BACKGROUND: Chronic pain is a complex condition that affects more than a quarter of people worldwide...

Machine learning-driven prediction of hospital admissions using gradient boosting and GPT-2.

BACKGROUND: Accurately predicting hospital admissions from the emergency department (ED) is essentia...

A comparative study of neuro-fuzzy and neural network models in predicting length of stay in university hospital.

BACKGROUND: The time a patient spends in the hospital from admission to discharge is known as the le...