Hospital-Based Medicine

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

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Implementation of a cloud-based referral platform in ophthalmology: making telemedicine services a reality in eye care.

BACKGROUND: Hospital Eye Services (HES) in the UK face an increasing number of optometric referrals ...

Incorporating Laboratory Values Into a Machine Learning Model Improves In-Hospital Mortality Predictions After Rapid Response Team Call.

OBJECTIVES: Machine learning models have been used to predict mortality among patients requiring rap...

On-field player workload exposure and knee injury risk monitoring via deep learning.

In sports analytics, an understanding of accurate on-field 3D knee joint moments (KJM) could provide...

Justifying diagnosis decisions by deep neural networks.

An integrated approach is proposed across visual and textual data to both determine and justify a me...

Predicting mechanical restraint of psychiatric inpatients by applying machine learning on electronic health data.

OBJECTIVE: Mechanical restraint (MR) is used to prevent patients from harming themselves or others d...

A Real-Time Early Warning System for Monitoring Inpatient Mortality Risk: Prospective Study Using Electronic Medical Record Data.

BACKGROUND: The rapid deterioration observed in the condition of some hospitalized patients can be a...

Machine Learning Approach to Inpatient Violence Risk Assessment Using Routinely Collected Clinical Notes in Electronic Health Records.

IMPORTANCE: Inpatient violence remains a significant problem despite existing risk assessment method...

Development of machine learning algorithms for prediction of mortality in spinal epidural abscess.

BACKGROUND CONTEXT: In-hospital and short-term mortality in patients with spinal epidural abscess (S...

Comparison of machine learning models for seizure prediction in hospitalized patients.

OBJECTIVE: To compare machine learning methods for predicting inpatient seizures risk and determine ...

Neural networks versus Logistic regression for 30 days all-cause readmission prediction.

Heart failure (HF) is one of the leading causes of hospital admissions in the US. Readmission within...

A Radical Proposition: Opioid-sparing Prostatectomy.

Radical prostatectomy has largely become a procedure requiring a single day in the hospital with imp...

Outcome prediction of out-of-hospital cardiac arrest with presumed cardiac aetiology using an advanced machine learning technique.

BACKGROUND: Outcome prediction for patients with out-of-hospital cardiac arrest (OHCA) has the possi...

Adjusting the dose in paediatric care: dispersing four different aspirin tablets and taking a proportion.

OBJECTIVES: When caring for children in a hospital setting, tablets are often manipulated at the war...

Quality of working life from the perspective of different groups of professionals working in a maternity hospital.

The relationship between people and work has a direct impact on quality of life and health. The obje...

FriWalk robotic walker: usability, acceptance and UX evaluation after a pilot study in a real environment.

: Scientific evidence supports that prevention strategies like multicomponent physical exercise help...

Deep-Learning Language-Modeling Approach for Automated, Personalized, and Iterative Radiology-Pathology Correlation.

PURPOSE: Radiology-pathology correlation has long been foundational to continuing education, peer le...

Predicting Inpatient Payments Prior to Lower Extremity Arthroplasty Using Deep Learning: Which Model Architecture Is Best?

BACKGROUND: Recent advances in machine learning have given rise to deep learning, which uses hierarc...

Detecting adverse drug reactions in discharge summaries of electronic medical records using Readpeer.

BACKGROUND: Hospital discharge summaries offer a potentially rich resource to enhance pharmacovigila...

Using a Multi-Task Recurrent Neural Network With Attention Mechanisms to Predict Hospital Mortality of Patients.

Estimating hospital mortality of patients is important in assisting clinicians to make decisions and...

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