Hospital-Based Medicine

Usefulness of Semisupervised Machine-Learning-Based Phenogrouping to Improve Risk Assessment for Patients Undergoing Transcatheter Aortic Valve Implantation.

Semisupervised machine-learning methods are able to learn from fewer labeled patient data. We illust...

How Good Is Machine Learning in Predicting All-Cause 30-Day Hospital Readmission? Evidence From Administrative Data.

OBJECTIVES: Hospital readmission is a main cost driver for healthcare systems, but existing works of...

Development, implementation, and prospective validation of a model to predict 60-day end-of-life in hospitalized adults upon admission at three sites.

BACKGROUND: Automated systems that use machine learning to estimate a patient's risk of death are be...

Hospital robotic use for colorectal cancer care.

The use of robotic surgery for colorectal cancer continues to increase. However, not all organizatio...

Implementation of Artificial Intelligence-Based Clinical Decision Support to Reduce Hospital Readmissions at a Regional Hospital.

BACKGROUND: Hospital readmissions are a key quality metric, which has been tied to reimbursement. On...

Machine learning and readmission: Do we need new methods to solve old problems?

Using social robot PLEO to enhance the well-being of hospitalised children.

Hospitalisation is stressful for children. Play material is often offered for distraction and comfor...

Artificial Intelligence-Driven Oncology Clinical Decision Support System for Multidisciplinary Teams.

Watson for Oncology (WfO) is a clinical decision support system driven by artificial intelligence. I...

Development of a clinical decision support system for severity risk prediction and triage of COVID-19 patients at hospital admission: an international multicentre study.

BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) has globally strained medical resour...

Between Always and Never: Evaluating Uncertainty in Radiology Reports Using Natural Language Processing.

The ideal radiology report reduces diagnostic uncertainty, while avoiding ambiguity whenever possibl...

Utilization of machine-learning models to accurately predict the risk for critical COVID-19.

Among patients with Coronavirus disease (COVID-19), the ability to identify patients at risk for det...

Predicting In-Hospital Mortality at Admission to the Medical Ward: A Big-Data Machine Learning Model.

BACKGROUND: General medical wards admit high-risk patients. Artificial intelligence algorithms can u...

Caregiver burden in stroke inpatients: a randomized study comparing robot-assisted gait training and conventional therapy.

The effects of caregiver burden during the inpatient rehabilitation period have not yet been investi...

A Single-Center Evaluation of Extended Infusion Piperacillin/Tazobactam for Empiric Treatment in the Intensive Care Unit.

Piperacillin/tazobactam (PTZ) extended infusion (EI) is often used empirically in the intensive car...

A fully automatic deep learning system for COVID-19 diagnostic and prognostic analysis.

Coronavirus disease 2019 (COVID-19) has spread globally, and medical resources become insufficient i...

Stroke prognostication for discharge planning with machine learning: A derivation study.

Post-stroke discharge planning may be aided by accurate early prognostication. Machine learning may ...

Development and validation of prognosis model of mortality risk in patients with COVID-19.

This study aimed to identify clinical features for prognosing mortality risk using machine-learning ...

Agent-oriented Decision Support System for Business Processes Management with Genetic Algorithm Optimization: an Application in Healthcare.

Agent-based approaches have been known to be appropriate as systems and methods in medical administr...

Artificial neural networks improve early outcome prediction and risk classification in out-of-hospital cardiac arrest patients admitted to intensive care.

BACKGROUND: Pre-hospital circumstances, cardiac arrest characteristics, comorbidities and clinical s...

Machine Learning Algorithms Identify Pathogen-Specific Biomarkers of Clinical and Metabolomic Characteristics in Septic Patients with Bacterial Infections.

Sepsis is a high-mortality disease that is infected by bacteria, but pathogens in individual patient...

Prediction of 1-Year Mortality from Acute Myocardial Infarction Using Machine Learning.

Risk stratification at hospital discharge could be instrumental in guiding postdischarge care. In th...