Hospital-Based Medicine

Latest AI and machine learning research in hospital-based medicine for healthcare professionals.

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Machine learning-based diagnostic model for stroke in non-neurological intensive care unit patients with acute neurological manifestations.

Stroke is a neurological complication that can occur in patients admitted to the intensive care unit...

External validation and performance analysis of a deep learning-based model for the detection of intracranial hemorrhage.

PurposeWe aimed to investigate the external validation and performance of an FDA-approved deep learn...

Assessing Visitor Expectations of AI Nursing Robots in Hospital Settings: Cross-Sectional Study Using the Kano Model.

BACKGROUND: Globally, the rates at which the aging population and the prevalence of chronic diseases...

Advancing healthcare through mobile collaboration: a survey of intelligent nursing robots research.

Mobile collaborative intelligent nursing robots have gained significant attention in the healthcare ...

Predicting Epidural Hematoma Expansion in Traumatic Brain Injury: A Machine Learning Approach.

IntroductionTraumatic brain injury (TBI) is a leading cause of disability and mortality worldwide, w...

Artificial intelligence-powered image analysis: A paradigm shift in infectious disease detection.

The global burden of infectious diseases significantly affects mortality rates, with their varying s...

Hospital Length of Stay Prediction for Planned Admissions Using Observational Medical Outcomes Partnership Common Data Model: Retrospective Study.

BACKGROUND: Accurate hospital length of stay (LoS) prediction enables efficient resource management....

Interpretable machine learning for time-to-event prediction in medicine and healthcare.

Time-to-event prediction, e.g. cancer survival analysis or hospital length of stay, is a highly prom...

Predictive model of in-hospital mortality in liver cirrhosis patients with hyponatremia: an artificial neural network approach.

Hyponatremia can worsen the outcomes of patients with liver cirrhosis. However, it remains unclear a...

Antimicrobial efficacy of an experimental UV-C robot in controlled conditions and in a real hospital scenario.

BACKGROUND: Among no-touch automated disinfection devices, ultraviolet-C (UV-C) radiation has been p...

Performance of deep learning models in predicting the nugent score to diagnose bacterial vaginosis.

The Nugent score is a commonly used diagnostic tool for bacterial vaginosis. However, its accuracy d...

Predictive risk models for COVID-19 patients using the multi-thresholding meta-algorithm.

This study aims to develop a Machine Learning model to assess the risks faced by COVID-19 patients i...

An interpretable machine learning scoring tool for estimating time to recurrence readmissions in stroke patients.

BACKGROUND: Stroke recurrence readmission poses an additional burden on both patients and healthcare...

Machine learning for predicting in-hospital mortality in elderly patients with heart failure combined with hypertension: a multicenter retrospective study.

BACKGROUND: Heart failure combined with hypertension is a major contributor for elderly patients (≥ ...

Extracting social determinants of health from inpatient electronic medical records using natural language processing.

BACKGROUND: Social determinants of health (SDOH) have been shown to be important predictors of healt...

Automatic face detection based on bidirectional recurrent neural network optimized by improved Ebola optimization search algorithm.

Face detection is a multidisciplinary research subject that employs fundamental computer algorithms,...

Critical care studies using large language models based on electronic healthcare records: A technical note.

The integration of large language models (LLMs) in clinical medicine, particularly in critical care,...

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