AIMC Topic: Prospective Studies

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Robotic-assisted hand therapy for improvement of hand function in children with cerebral palsy: a case series study.

European journal of physical and rehabilitation medicine
BACKGROUND: Most types of robot-assisted training (RT) have been used in Cerebral Palsy (CP) patients only focus on proximal upper extremity. Few of study investigated the effect of distal upper extremity training.

Using machine learning methods to determine a typology of patients with HIV-HCV infection to be treated with antivirals.

PloS one
Several European countries have established criteria for prioritising initiation of treatment in patients infected with the hepatitis C virus (HCV) by grouping patients according to clinical characteristics. Based on neural network techniques, our ob...

Artificial intelligence for diagnosis and grading of prostate cancer in biopsies: a population-based, diagnostic study.

The Lancet. Oncology
BACKGROUND: An increasing volume of prostate biopsies and a worldwide shortage of urological pathologists puts a strain on pathology departments. Additionally, the high intra-observer and inter-observer variability in grading can result in overtreatm...

The impact of machine learning on patient care: A systematic review.

Artificial intelligence in medicine
BACKGROUND: Despite the expanding use of machine learning (ML) in fields such as finance and marketing, its application in the daily practice of clinical medicine is almost non-existent. In this systematic review, we describe the various areas within...

Ensemble Learning for Early-Response Prediction of Antidepressant Treatment in Major Depressive Disorder.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: In order to reduce unsuccessful treatment trials for depression, neuroimaging and genetic information can be considered as biomarkers. Together with machine-learning methods, prediction models have proved to be valuable for baseline predi...

A validation of machine learning-based risk scores in the prehospital setting.

PloS one
BACKGROUND: The triage of patients in prehospital care is a difficult task, and improved risk assessment tools are needed both at the dispatch center and on the ambulance to differentiate between low- and high-risk patients. This study validates a ma...

Machine learning based quantification of ejection and filling parameters by fully automated dynamic measurement of left ventricular volumes from cardiac magnetic resonance images.

Magnetic resonance imaging
BACKGROUND: Although analysis of cardiac magnetic resonance (CMR) images provides accurate and reproducible measurements of left ventricular (LV) volumes, these measurements are usually not performed throughout the cardiac cycle because of lack of to...