Hospital-Based Medicine

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

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Deep Feature Learning from a Hospital-Scale Chest X-ray Dataset with Application to TB Detection on a Small-Scale Dataset.

The use of ImageNet pre-trained networks is becoming widespread in the medical imaging community. It...

Class Imbalance Impact on the Prediction of Complications during Home Hospitalization: A Comparative Study.

Home hospitalization (HH) is presented as a healthcare alternative capable of providing high standar...

Sparse Embedding for Interpretable Hospital Admission Prediction.

This paper introduces a sparse embedding for electronic health record (EHR) data in order to predict...

Predicting Gastrointestinal Bleeding Events from Multimodal In-Hospital Electronic Health Records Using Deep Fusion Networks.

Applying machine learning (ML) methods on electronic health records (EHRs) that accurately predict t...

Application of Machine Learning to Prediction of Surgical Site Infection.

Surgical site infections are an important health concern, particularly in low-resource areas, where ...

Machine Learning-based Risk of Hospital Readmissions: Predicting Acute Readmissions within 30 Days of Discharge.

The objective of this study was to design and develop a 30-day risk of hospital readmission predicti...

Monitoring of Patient Blanket Coverage using 3D Camera Data.

Nurses in a hospital are responsible for the monitoring and care of a large number of patients. Regu...

Borderline Personality Features in Inpatients with Bipolar Disorder: Impact on Course and Machine Learning Model Use to Predict Rapid Readmission.

BACKGROUND: Earlier research indicated that nearly 20% of patients diagnosed with either bipolar dis...

Social Robots for Hospitalized Children.

BACKGROUND AND OBJECTIVES: Social robots (SRs) are increasingly present in medical and educational c...

Artificial neural networks can predict trauma volume and acuity regardless of center size and geography: A multicenter study.

BACKGROUND: Trauma has long been considered unpredictable. Artificial neural networks (ANN) have rec...

A Predictive Model for Determining Patients Not Requiring Prolonged Hospital Length of Stay After Elective Primary Total Hip Arthroplasty.

BACKGROUND: Hospital length of stay (LOS) is an important quality metric for total hip arthroplasty....

Machine learning-based preoperative predictive analytics for lumbar spinal stenosis.

OBJECTIVEPatient-reported outcome measures (PROMs) following decompression surgery for lumbar spinal...

Nurses "Seeing Forest for the Trees" in the Age of Machine Learning: Using Nursing Knowledge to Improve Relevance and Performance.

Although machine learning is increasingly being applied to support clinical decision making, there i...

Supervised machine learning for the prediction of infection on admission to hospital: a prospective observational cohort study.

BACKGROUND: Infection diagnosis can be challenging, relying on clinical judgement and non-specific m...

A centralized automated-dispensing system in a French teaching hospital: return on investment and quality improvement.

OBJECTIVES: To evaluate the return on investment (ROI) and quality improvement after implementation ...

Medical assertion classification in Chinese EMRs using attention enhanced neural network.

Electronic medical records (EMRs), such as hospital discharge summaries, contain a wealth of informa...

Determinants of In-Hospital Mortality After Percutaneous Coronary Intervention: A Machine Learning Approach.

Background The ability to accurately predict the occurrence of in-hospital death after percutaneous ...

Fuzzy logic and hospital admission due to respiratory diseases using estimated values by mathematical model.

Hospitalizations due to respiratory diseases generate financial costs for the Health System in addit...

The 18th FRAME Annual Lecture, October 2019: Human Trials in Pharmacology.

Safety and efficacy testing is a crucial part of the drug development process, and several different...

Developing a Social Robot - A Case Study.

Social robotics is currently challenging researchers to look at virtually every topic with relevance...

Artificial intelligence, machine learning, computer-aided diagnosis, and radiomics: advances in imaging towards to precision medicine.

The discipline of radiology and diagnostic imaging has evolved greatly in recent years. We have obse...

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