AI Medical Compendium Topic:
Supervised Machine Learning

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Teleconsultations between Patients and Healthcare Professionals in Primary Care in Catalonia: The Evaluation of Text Classification Algorithms Using Supervised Machine Learning.

International journal of environmental research and public health
: The primary care service in Catalonia has operated an asynchronous teleconsulting service between GPs and patients since 2015 (eConsulta), which has generated some 500,000 messages. New developments in big data analysis tools, particularly those in...

Performance Analysis of Boosting Classifiers in Recognizing Activities of Daily Living.

International journal of environmental research and public health
Physical activity is essential for physical and mental health, and its absence is highly associated with severe health conditions and disorders. Therefore, tracking activities of daily living can help promote quality of life. Wearable sensors in this...

Pyramid feature adaptation for semi-supervised cardiac bi-ventricle segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Cardiac bi-ventricle segmentation (BVS) is an essential task for assessing cardiac indices, such as the ejection fraction and volume of the left ventricle (LV) and right ventricle (RV). However, BVS is extremely challenging due to the high variabilit...

Accuracy of a machine learning muscle MRI-based tool for the diagnosis of muscular dystrophies.

Neurology
OBJECTIVE: Genetic diagnosis of muscular dystrophies (MDs) has classically been guided by clinical presentation, muscle biopsy, and muscle MRI data. Muscle MRI suggests diagnosis based on the pattern of muscle fatty replacement. However, patterns ove...

Machine learning for syndromic surveillance using veterinary necropsy reports.

PloS one
The use of natural language data for animal population surveillance represents a valuable opportunity to gather information about potential disease outbreaks, emerging zoonotic diseases, or bioterrorism threats. In this study, we evaluate machine lea...

Learning metal artifact reduction in cardiac CT images with moving pacemakers.

Medical image analysis
Metal objects in the human heart such as implanted pacemakers frequently lead to heavy artifacts in reconstructed CT image volumes. Due to cardiac motion, common metal artifact reduction methods which assume a static object during CT acquisition are ...

Quantitative Thermal Imaging Biomarkers to Detect Acute Skin Toxicity From Breast Radiation Therapy Using Supervised Machine Learning.

International journal of radiation oncology, biology, physics
PURPOSE: Radiation-induced dermatitis is a common side effect of breast radiation therapy (RT). Current methods to evaluate breast skin toxicity include clinical examination, visual inspection, and patient-reported symptoms. Physiological changes ass...

Application of data mining in a cohort of Italian subjects undergoing myocardial perfusion imaging at an academic medical center.

Computer methods and programs in biomedicine
INTRODUCTION: Coronary artery disease (CAD) is still one of the primary causes of death in the developed countries. Stress single-photon emission computed tomography is used to evaluate myocardial perfusion and ventricular function in patients with s...

Semi-supervised learning for automatic segmentation of the knee from MRI with convolutional neural networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Segmentation is a crucial step in multiple biomechanics and orthopedics applications. The time-intensiveness and expertise requirements of medical image segmentation present a significant bottleneck for corresponding workflo...