AIMC Topic: Netherlands

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A Nationwide Study of Clinical Outcomes After Robot-Assisted Coronary Artery Bypass Surgery and Hybrid Revascularization in the Netherlands.

Innovations (Philadelphia, Pa.)
OBJECTIVE: Robot-assisted minimally invasive direct coronary artery bypass (RA-MIDCAB) surgery and hybrid coronary revascularization (HCR) are minimally invasive alternative strategies to conventional coronary artery bypass surgery in patients with i...

A machine learning approach to small area estimation: predicting the health, housing and well-being of the population of Netherlands.

International journal of health geographics
BACKGROUND: Local policymakers require information about public health, housing and well-being at small geographical areas. A municipality can for example use this information to organize targeted activities with the aim of improving the well-being o...

The Potential Cost-Effectiveness of a Machine Learning Tool That Can Prevent Untimely Intensive Care Unit Discharge.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
OBJECTIVES: The machine learning prediction model Pacmed Critical (PC), currently under development, may guide intensivists in their decision-making process on the most appropriate time to discharge a patient from the intensive care unit (ICU). Given...

Do People Favor Artificial Intelligence Over Physicians? A Survey Among the General Population and Their View on Artificial Intelligence in Medicine.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
OBJECTIVES: To investigate the general population's view on artificial intelligence (AI) in medicine with specific emphasis on 3 areas that have experienced major progress in AI research in the past few years, namely radiology, robotic surgery, and d...

Predicting Future Service Use in Dutch Mental Healthcare: A Machine Learning Approach.

Administration and policy in mental health
A mental healthcare system in which the scarce resources are equitably and efficiently allocated, benefits from a predictive model about expected service use. The skewness in service use is a challenge for such models. In this study, we applied a mac...

Deep-learning based monitoring of FOG layer dynamics in wastewater pumping stations.

Water research
Accumulation of fat, oil and grease (FOG) in the sumps of wastewater pumping stations is a common failure cause for these facilities. Floating solids are often not transported by the pump suction inlets and the individual solids can accumulate to sti...

Intermediate-term survival of robot-assisted versus open radical cystectomy for muscle-invasive and high-risk non-muscle invasive bladder cancer in The Netherlands.

Urologic oncology
BACKGROUND: Radical cystectomy with pelvic lymph node dissection is the recommended treatment in non-metastatic muscle-invasive bladder cancer (MIBC). In randomised trials, robot-assisted radical cystectomy (RARC) showed non-inferior short-term oncol...

Understanding importance of clinical biomarkers for diagnosis of anxiety disorders using machine learning models.

PloS one
Anxiety disorders are a group of mental illnesses that cause constant and overwhelming feelings of anxiety and fear. Excessive anxiety can make an individual avoid work, school, family get-togethers, and other social situations that in turn might amp...

Explainable machine learning can outperform Cox regression predictions and provide insights in breast cancer survival.

Scientific reports
Cox Proportional Hazards (CPH) analysis is the standard for survival analysis in oncology. Recently, several machine learning (ML) techniques have been adapted for this task. Although they have shown to yield results at least as good as classical met...