Hospital-Based Medicine

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

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Showing 1828-1848 of 9,930 articles
Using an artificial neural network to predict traumatic brain injury.

In BriefPediatric traumatic brain injury (TBI) is common, but not all injuries require hospitalizati...

Assessment of Time-Series Machine Learning Methods for Forecasting Hospital Discharge Volume.

IMPORTANCE: Forecasting the volume of hospital discharges has important implications for resource al...

RSDNet: Learning to Predict Remaining Surgery Duration from Laparoscopic Videos Without Manual Annotations.

Accurate surgery duration estimation is necessary for optimal OR planning, which plays an important ...

Low vitamin D at ICU admission is associated with cancer, infections, acute respiratory insufficiency, and liver failure.

OBJECTIVES: Vitamin D deficiency may be associated with comorbidities and poor prognosis. However, t...

Using clinical Natural Language Processing for health outcomes research: Overview and actionable suggestions for future advances.

The importance of incorporating Natural Language Processing (NLP) methods in clinical informatics re...

SCREEN-DR: Collaborative platform for diabetic retinopathy.

BACKGROUND AND OBJECTIVE: Diabetic retinopathy (DR) is the most prevalent microvascular complication...

Vitamin D status in relation to age, bone mineral density of the spine and femur in obese Saudi females - A hospital-based study.

The aim of the present study was to evaluate the association between Bone mineral density in lumber ...

Identifying in Palliative Care Consultations: A Tandem Machine-Learning and Human Coding Method.

Systematic measurement of conversational features in the natural clinical setting is essential to b...

[Hepatitis B and renal failure: prevalence and associated factors in National University Hospital Center of Cotonou].

INTRODUCTION: the association between the kidneys and hepatitis B is complex. This study aims to det...

An improved support vector machine-based diabetic readmission prediction.

BACKGROUND AND OBJECTIVE: In healthcare systems, the cost of unplanned readmission accounts for a la...

Predicting hospital associated disability from imbalanced data using supervised learning.

Hospitalization of elderly patients can lead to serious adverse effects on their functional capabili...

Sociomarkers and biomarkers: predictive modeling in identifying pediatric asthma patients at risk of hospital revisits.

The importance of social components of health has been emphasized both in epidemiology and public he...

Using Artificial Intelligence (Watson for Oncology) for Treatment Recommendations Amongst Chinese Patients with Lung Cancer: Feasibility Study.

BACKGROUND: Artificial intelligence (AI) is developing quickly in the medical field and can benefit ...

Identify and monitor clinical variation using machine intelligence: a pilot in colorectal surgery.

Standardized clinical pathways are useful tool to reduce variation in clinical management and may im...

The Combined Use of Transcranial Direct Current Stimulation and Robotic Therapy for the Upper Limb.

Neurologic disorders such as stroke and cerebral palsy are leading causes of long-term disability an...

Improving Prediction of Risk of Hospital Admission in Chronic Obstructive Pulmonary Disease: Application of Machine Learning to Telemonitoring Data.

BACKGROUND: Telemonitoring of symptoms and physiological signs has been suggested as a means of earl...

A machine learning-based model for 1-year mortality prediction in patients admitted to an Intensive Care Unit with a diagnosis of sepsis.

INTRODUCTION: Sepsis is associated to a high mortality rate, and its severity must be evaluated quic...

Predicting the risk of acute care readmissions among rehabilitation inpatients: A machine learning approach.

INTRODUCTION: Readmission from inpatient rehabilitation facilities to acute care hospitals is a seri...

Machine Learning and Primary Total Knee Arthroplasty: Patient Forecasting for a Patient-Specific Payment Model.

BACKGROUND: Value-based and patient-specific care represent 2 critical areas of focus that have yet ...

Societal Issues Concerning the Application of Artificial Intelligence in Medicine.

BACKGROUND: Medicine is becoming an increasingly data-centred discipline and, beyond classical stati...

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