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Classification of Depression Patients and Normal Subjects Based on Electroencephalogram (EEG) Signal Using Alpha Power and Theta Asymmetry.

Journal of medical systems
Depression or Major Depressive Disorder (MDD) is a mental illness which negatively affects how a person thinks, acts or feels. MDD has become a major disease affecting millions of people presently. The diagnosis of depression is questionnaire based a...

Morphological Neuroimaging Biomarkers for Tinnitus: Evidence Obtained by Applying Machine Learning.

Neural plasticity
According to previous studies, many neuroanatomical alterations have been detected in patients with tinnitus. However, the results of these studies have been inconsistent. The objective of this study was to explore the cortical/subcortical morphologi...

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...

Predicting the occurrence of surgical site infections using text mining and machine learning.

PloS one
In this study we propose the use of text mining and machine learning methods to predict and detect Surgical Site Infections (SSIs) using textual descriptions of surgeries and post-operative patients' records, mined from the database of a high complex...

Emotion recognition from posed and spontaneous dynamic expressions: Human observers versus machine analysis.

Emotion (Washington, D.C.)
The majority of research on the judgment of emotion from facial expressions has focused on deliberately posed displays, often sampled from single stimulus sets. Herein, we investigate emotion recognition from posed and spontaneous expressions, compar...

Machine learning methods are comparable to logistic regression techniques in predicting severe walking limitation following total knee arthroplasty.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: Machine-learning methods are flexible prediction algorithms with potential advantages over conventional regression. This study aimed to use machine learning methods to predict post-total knee arthroplasty (TKA) walking limitation, and to com...

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...

Artificial intelligence and neural networks in urology: current clinical applications.

Minerva urologica e nefrologica = The Italian journal of urology and nephrology
INTRODUCTION: As we enter the era of "big data," an increasing amount of complex health-care data will become available. These data are often redundant, "noisy," and characterized by wide variability. In order to offer a precise and transversal view ...

A modular cGAN classification framework: Application to colorectal tumor detection.

Scientific reports
Automatic identification of tissue structures in the analysis of digital tissue biopsies remains an ongoing problem in digital pathology. Common barriers include lack of reliable ground truth due to inter- and intra- reader variability, class imbalan...