Hospital-Based Medicine

Infection Control

Latest AI and machine learning research in infection control for healthcare professionals.

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The safe introduction of robotic surgery in a free-standing children's hospital.

The aim of this study is to report the experience of implementing a pediatric robotic surgery progra...

Deep Learning on Electrocardiograms for Prediction of In-hospital Intradialytic Hypotension in Patients with ESKD.

Intradialytic hypotension is common in patients who are on hemodialysis. We applied deep learning te...

Proportionally Fair Hospital Collaborations in Federated Learning of Histopathology Images.

Medical centers and healthcare providers have concerns and hence restrictions around sharing data wi...

Infection diagnosis in hydrocephalus CT images: a domain enriched attention learning approach.

. Hydrocephalus is the leading indication for pediatric neurosurgical care worldwide. Identification...

LGTRL-DE: Local and Global Temporal Representation Learning with Demographic Embedding for in-hospital mortality prediction.

Predicting the patient's in-hospital mortality from the historical Electronic Medical Records (EMRs)...

Explainable COVID-19 Detection Based on Chest X-rays Using an End-to-End RegNet Architecture.

COVID-19,which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is one...

Interpretable machine learning models for hospital readmission prediction: a two-step extracted regression tree approach.

BACKGROUND: Advanced machine learning models have received wide attention in assisting medical decis...

Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii.

Acinetobacter baumannii is a nosocomial Gram-negative pathogen that often displays multidrug resista...

A Machine Learning Prediction Model for Non-cardiogenic Out-of-hospital Cardiac Arrest with Initial Non-shockable Rhythm.

OBJECTIVES: The purpose of this study was to develop and validate a machine learning prediction mode...

Evaluation of cancer drug infusion devices prior to the implementation of a compounding robot.

INTRODUCTION: Compounding robots are increasingly being implemented in hospital pharmacies. In our h...

The implementation of a real time early warning system using machine learning in an Australian hospital to improve patient outcomes.

BACKGROUND: Early Warning Scores (EWS) monitor inpatient deterioration predominantly using vital sig...

Deep Learning vs Traditional Models for Predicting Hospital Readmission among Patients with Diabetes.

A hospital readmission risk prediction tool for patients with diabetes based on electronic health re...

[Robotic production of injectable anticancer drugs in hospital pharmacies].

INTRODUCTION: Following the 2005 decree on securing the medicine supply chain, the production of "ch...

Comparison of correctly and incorrectly classified patients for in-hospital mortality prediction in the intensive care unit.

BACKGROUND: The use of machine learning is becoming increasingly popular in many disciplines, but th...

Hospital mortality prediction in traumatic injuries patients: comparing different SMOTE-based machine learning algorithms.

BACKGROUND: Trauma is one of the most critical public health issues worldwide, leading to death and ...

Machine Learning Model for Assessment of Risk Factors and Postoperative Day for Superficial vs Deep/Organ-Space Surgical Site Infections.

Deep and organ space surgical site infections (SSI) require more intensive treatment, may result in...

Utilization of Bioinorganic Nanodrugs and Nanomaterials for the Control of Infectious Diseases Using Deep Learning.

As one of the main causes of morbidity and mortality, viral infections have a major impact on the we...

A Hybrid Stacked CNN and Residual Feedback GMDH-LSTM Deep Learning Model for Stroke Prediction Applied on Mobile AI Smart Hospital Platform.

Artificial intelligence (AI) techniques for intelligent mobile computing in healthcare has opened up...

Predicting heart failure in-hospital mortality by integrating longitudinal and category data in electronic health records.

Heart failure is a life-threatening syndrome that is diagnosed in 3.6 million people worldwide each ...

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