AIMC Topic: Male

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A robot-based behavioural task to quantify impairments in rapid motor decisions and actions after stroke.

Journal of neuroengineering and rehabilitation
BACKGROUND: Stroke can affect our ability to perform daily activities, although it can be difficult to identify the underlying functional impairment(s). Recent theories highlight the importance of sensory feedback in selecting future motor actions. T...

A Multicenter Study of Early Anti-inflammatory Treatment in Patients With Acute Anterior Cruciate Ligament Tear.

The American journal of sports medicine
BACKGROUND: It is increasingly recognized that biochemical abnormalities of the joint precede radiographic abnormalities of posttraumatic osteoarthritis (PTOA) by as much as decades. A growing body of evidence strongly suggests that the progression f...

Support vector machine classification of arterial volume-weighted arterial spin tagging images.

Brain and behavior
INTRODUCTION: In recent years, machine-learning techniques have gained growing popularity in medical image analysis. Temporal brain-state classification is one of the major applications of machine-learning techniques in functional magnetic resonance ...

Multi-parameter machine learning approach to the neuroanatomical basis of developmental dyslexia.

Human brain mapping
Despite decades of research, the anatomical abnormalities associated with developmental dyslexia are still not fully described. Studies have focused on between-group comparisons in which different neuroanatomical measures were generally explored in i...

Stop! border ahead: Automatic detection of subthalamic exit during deep brain stimulation surgery.

Movement disorders : official journal of the Movement Disorder Society
BACKGROUND: Microelectrode recordings along preplanned trajectories are often used for accurate definition of the subthalamic nucleus (STN) borders during deep brain stimulation (DBS) surgery for Parkinson's disease. Usually, the demarcation of the S...

Successful classification of cocaine dependence using brain imaging: a generalizable machine learning approach.

BMC bioinformatics
BACKGROUND: Neuroimaging studies have yielded significant advances in the understanding of neural processes relevant to the development and persistence of addiction. However, these advances have not explored extensively for diagnostic accuracy in hum...

Individual prediction of long-term outcome in adolescents at ultra-high risk for psychosis: Applying machine learning techniques to brain imaging data.

Human brain mapping
An important focus of studies of individuals at ultra-high risk (UHR) for psychosis has been to identify biomarkers to predict which individuals will transition to psychosis. However, the majority of individuals will prove to be resilient and go on t...

Computer-aided diagnosis system for lung nodules based on computed tomography using shape analysis, a genetic algorithm, and SVM.

Medical & biological engineering & computing
Lung cancer is the major cause of death among patients with cancer worldwide. This work is intended to develop a methodology for the diagnosis of lung nodules using images from the Image Database Consortium and Image Database Resource Initiative (LID...

Evaluation of supervised machine-learning algorithms to distinguish between inflammatory bowel disease and alimentary lymphoma in cats.

Journal of veterinary diagnostic investigation : official publication of the American Association of Veterinary Laboratory Diagnosticians, Inc
Inflammatory bowel disease (IBD) and alimentary lymphoma (ALA) are common gastrointestinal diseases in cats. The very similar clinical signs and histopathologic features of these diseases make the distinction between them diagnostically challenging. ...