AIMC Topic: Adult

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Automating the process of identifying the preferred representational system in Neuro Linguistic Programming using Natural Language Processing.

Cognitive processing
Neuro Linguistic Programming (NLP) is a methodology used for recognition of human behavioral patterns and modification of the behavior. A significant part of this process is influenced by the theory of representational systems which equates to the fi...

Improving Reliability of Myocontrol Using Formal Verification.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
In the context of assistive robotics, myocontrol is one of the so-far unsolved problems of upper-limb prosthetics. It consists of swiftly, naturally, and reliably converting biosignals, non-invasively gathered from an upper-limb disabled subject, int...

Relative Factors Analysis of Imatinib Trough Concentration in Chinese Patients with Gastrointestinal Stromal Tumor.

Chemotherapy
AIMS: Imatinib plasma trough levels (IM Cmin) have been reported to have a considerable clinical impact in patients with gastrointestinal stromal tumors (GISTs). We therefore have investigated the factors affecting IM plasma concentration in Chinese ...

Characterization of clot composition in acute cerebral infarct using machine learning techniques.

Annals of clinical and translational neurology
OBJECTIVE: Clot characteristics can provide information on the cause of cerebral artery occlusion and may guide acute revascularization and secondary prevention strategies. We developed a rapid automated clot analysis system using machine learning (M...

Portable brain-computer interface based on novel convolutional neural network.

Computers in biology and medicine
Electroencephalography (EEG) is a powerful, noninvasive tool that provides a high temporal resolution to directly reflect brain activities. Conventional electrodes require skin preparation and the use of conductive gels, while subjects must wear unco...

Breast Microcalcification Diagnosis Using Deep Convolutional Neural Network from Digital Mammograms.

Computational and mathematical methods in medicine
Mammography is successfully used as an effective screening tool for cancer diagnosis. A calcification cluster on mammography is a primary sign of cancer. Early researches have proved the diagnostic value of the calcification, yet their performance is...

Does integral affect influence intentions to use artificial intelligence for skin cancer screening? A test of the affect heuristic.

Psychology & health
This study investigated how influences people's processing of messages about risks and benefits of using autonomous artificial intelligence (AI) technology to screen for skin cancer. We examined (emotion derived during decision making) separately ...

Classification of radiologically isolated syndrome and clinically isolated syndrome with machine-learning techniques.

European journal of neurology
BACKGROUND AND PURPOSE: The unanticipated detection by magnetic resonance imaging (MRI) in the brain of asymptomatic subjects of white matter lesions suggestive of multiple sclerosis (MS) has been named radiologically isolated syndrome (RIS). As the ...

Novel Machine Learning Identifies Brain Patterns Distinguishing Diagnostic Membership of Human Immunodeficiency Virus, Alcoholism, and Their Comorbidity of Individuals.

Biological psychiatry. Cognitive neuroscience and neuroimaging
The incidence of alcohol use disorder (AUD) in human immunodeficiency virus (HIV) infection is twice that of the rest of the population. This study documents complex radiologically identified, neuroanatomical effects of AUD+HIV comorbidity by identif...