Hospital-Based Medicine

Intelligent Recognition of Hospital Image Based on Deep Learning: The Relationship between Adaptive Behavior and Family Function in Children with ADHD.

Chronic diseases are gradually becoming the main threat to human health. By designing an efficient h...

Performance evaluation of Emergency Department patient arrivals forecasting models by including meteorological and calendar information: A comparative study.

The volume of daily patient arrivals at Emergency Departments (EDs) is unpredictable and is a signif...

Hybridized neural networks for non-invasive and continuous mortality risk assessment in neonates.

Premature birth is the primary risk factor in neonatal deaths, with the majority of extremely premat...

Gaining Insights Into Patient Satisfaction Through Interpretable Machine Learning.

Patient satisfaction is a key performance indicator of patient-centered care and hospital reimbursem...

Improving hospital readmission prediction using individualized utility analysis.

OBJECTIVE: Machine learning (ML) models for allocating readmission-mitigating interventions are typi...

The use of a UV-C disinfection robot in the routine cleaning process: a field study in an Academic hospital.

BACKGROUND: Environmental surface decontamination is a crucial tool to prevent the spread of infecti...

Prediction of Major Complications and Readmission After Lumbar Spinal Fusion: A Machine Learning-Driven Approach.

BACKGROUND: Given the significant cost and morbidity of patients undergoing lumbar fusion, accurate ...

Authors' Reply to: Minimizing Selection and Classification Biases Comment on "Clinical Characteristics and Prognostic Factors for Intensive Care Unit Admission of Patients With COVID-19: Retrospective Study Using Machine Learning and Natural Language Processing".

Minimizing Selection and Classification Biases. Comment on "Clinical Characteristics and Prognostic Factors for Intensive Care Unit Admission of Patients With COVID-19: Retrospective Study Using Machine Learning and Natural Language Processing".

Economic and utilization outcomes of medication management at a large Medicaid plan with disease management pharmacists using a novel artificial intelligence platform from 2018 to 2019: a retrospective observational study using regression methods.

Medication therapy management (MTM) and comprehensive medication management (CMM) have been practic...

Prediction of Bedridden Duration of Hospitalized Patients by Machine Learning Based on EMRs at Admission.

Being bedridden is a frequent comorbid condition that leads to a series of complications in clinical...

Leveraging electronic health record data to inform hospital resource management : A systematic data mining approach.

Early identification of resource needs is instrumental in promoting efficient hospital resource mana...

Multidisciplinary Approach to Robotic Resection of Abdominal Wall Endometriosis and Mesh Repair.

STUDY OBJECTIVE: To demonstrate a technique for robot-assisted laparoscopic excision of abdominal wa...

Machine Learning Algorithm Identifies the Importance of Environmental Factors for Hospital Discharge to Home of Stroke Patients using Wheelchair after Discharge.

BACKGROUND AND PURPOSE: Physical environmental factors are generally likely to become barriers for d...

Hidden Fluids in Plain Sight: Identifying Intravenous Medication Classes as Contributors to Intensive Care Unit Fluid Intake.

Fluid stewardship targets optimal fluid management to improve patient outcomes. Intravenous (IV) me...

Is there a difference between navigated and non-navigated robot cohorts in robot-assisted spine surgery? A multicenter, propensity-matched analysis of 2,800 screws and 372 patients.

BACKGROUND CONTEXT: Robot-assisted spine surgery continues to rapidly develop as evidenced by the gr...

Artificial Intelligence in magnetic Resonance guided Radiotherapy: Medical and physical considerations on state of art and future perspectives.

Over the last years, technological innovation in Radiotherapy (RT) led to the introduction of Magnet...

Blending Knowledge in Deep Recurrent Networks for Adverse Event Prediction at Hospital Discharge.

Deep learning architectures have an extremely high-capacity for modeling complex data in a wide vari...

Comparison of machine-learning methodologies for accurate diagnosis of sepsis using microarray gene expression data.

We investigate the feasibility of molecular-level sample classification of sepsis using microarray g...

OASIS +: leveraging machine learning to improve the prognostic accuracy of OASIS severity score for predicting in-hospital mortality.

BACKGROUND: Severity scores assess the acuity of critical illness by penalizing for the deviation of...

Gender blindness: On health and welfare technology, AI and gender equality in community care.

Digital health and welfare technologies and artificial intelligence are proposed to revolutionise he...