Hospital-Based Medicine

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 management. Hospital information systems, and electronic health records (EHR) in particular, collect valuable demographic and clinical patient data from the moment patients are admitted, which can help predict expected resource needs in early stages of patient episodes. To this end, this article propose...

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 wall endometriosis and mesh reinforcement of the subsequent defect.

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 discharge to home of wheelchair users, compared wit...

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) medications, flushes, and blood products, collective...

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 growing literature in recent years. In addition to d...

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 Magnetic Resonance-guided RT (MRgRT) systems. Due to the...

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 gene expression data merged by in silico meta-analy...

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 variety of domains. However, these architectures have ...

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 healthcare systems around the world by enabling new ...

Development of the Joint Commission of Taiwan's Smart Healthcare Standard.

It is well known that information technology (IT) can play a pivotal role in enhancing healthcare quality and patient safety. The use of computational...

Development and Validation of Machine Learning Models to Predict Admission From Emergency Department to Inpatient and Intensive Care Units.

STUDY OBJECTIVE: This study aimed to develop and validate 2 machine learning models that use historical and current-visit patient data from electronic...

Artificial intelligence in oncology: Path to implementation.

In recent years, the field of artificial intelligence (AI) in oncology has grown exponentially. AI solutions have been developed to tackle a variety o...

Application of machine learning in predicting hospital readmissions: a scoping review of the literature.

BACKGROUND: Advances in machine learning (ML) provide great opportunities in the prediction of hospital readmission. This review synthesizes the liter...

Use of deep learning to develop continuous-risk models for adverse event prediction from electronic health records.

Early prediction of patient outcomes is important for targeting preventive care. This protocol describes a practical workflow for developing deep-lear...

Machine learning analysis: general features, requirements and cardiovascular applications.

Artificial intelligence represents the science which will probably change the future of medicine by solving actually challenging issues. In this speci...

Adjuvant Therapy System of COVID-19 Patient: Integrating Warning, Therapy, Post-Therapy Psychological Intervention.

The 2019 novel coronavirus(COVID-19) spreads rapidly, and the large-scale infection leads to the lack of medical resources. For the purpose of providi...

Machine learning-based mortality prediction model for heat-related illness.

In this study, we aimed to develop and validate a machine learning-based mortality prediction model for hospitalized heat-related illness patients. Af...

Recent progress of robotic head and neck surgery using a flexible single port robotic system.

We performed robotic neck surgery through a transoral or retroauricular approach (RA) using the DaVinci SP and analyzed our experiences to evaluate th...

Diagnostic and prognostic capabilities of a biomarker and EMR-based machine learning algorithm for sepsis.

Sepsis is a major cause of mortality among hospitalized patients worldwide. Shorter time to administration of broad-spectrum antibiotics is associated...

Reducing Loneliness in Stationary Geriatric Care with Robots and Virtual Encounters-A Contribution to the COVID-19 Pandemic.

The bans on visiting nursing homes during the COVID-19 pandemic, while intended to protect residents, also have the risk of increasing the loneliness ...