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Prediction of Multidrug-Resistant TB from CT Pulmonary Images Based on Deep Learning Techniques.

Molecular pharmaceutics Jan 29, 2018
While tuberculosis (TB) disease was discovered more than a century ago, it has not been eradicated yet. Quite contrary, at present, TB constitutes one of the top 10 causes of death and has shown signs of increasing. To complement the conventional dia...
Deep Learning Support Vector Machine Tuberculosis, Multidrug-Resistant Humans Neural Networks, Computer Tomography, X-Ray Computed
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Machine learning to parse breast pathology reports in Chinese.

Breast cancer research and treatment Jan 29, 2018
INTRODUCTION: Large structured databases of pathology findings are valuable in deriving new clinical insights. However, they are labor intensive to create and generally require manual annotation. There has been some work in the bioinformatics communi...
Humans Data Mining Machine Learning Algorithms Breast Neoplasms Natural Language Processing Breast Databases, Factual Electronic Health Records Female
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Machine Learning Approaches for Clinical Psychology and Psychiatry.

Annual review of clinical psychology Jan 29, 2018
Machine learning approaches for clinical psychology and psychiatry explicitly focus on learning statistical functions from multidimensional data sets to make generalizable predictions about individuals. The goal of this review is to provide an access...
Mental Disorders Psychology, Clinical Humans Psychiatry Machine Learning Precision Medicine
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Machine Learning EEG to Predict Cognitive Functioning and Processing Speed Over a 2-Year Period in Multiple Sclerosis Patients and Controls.

Brain topography Jan 29, 2018
Event-related potentials (ERPs) show promise to be objective indicators of cognitive functioning. The aim of the study was to examine if ERPs recorded during an oddball task would predict cognitive functioning and information processing speed in Mult...
Neuropsychological Tests Scalp Cognition Electroencephalography Multiple Sclerosis Male Middle Aged Humans Machine Learning Brain Female Adult
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In Schizophrenia, Depression, Anxiety, and Physiosomatic Symptoms Are Strongly Related to Psychotic Symptoms and Excitation, Impairments in Episodic Memory, and Increased Production of Neurotoxic Tryptophan Catabolites: a Multivariate and Machine Learning Study.

Neurotoxicity research Jan 29, 2018
The depression, anxiety and physiosomatic symptoms (DAPS) of schizophrenia are associated with negative symptoms and changes in tryptophan catabolite (TRYCAT) patterning. The aim of this study is to delineate the associations between DAPS and psychos...
Memory Disorders Multivariate Analysis Medically Unexplained Symptoms Depression Humans Adolescent Tryptophan Machine Learning Male Anxiety Female Aged Middle Aged Psychiatric Status Rating Scales Young Adult Thailand Adult
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Risk-Predicting Model for Incident of Essential Hypertension Based on Environmental and Genetic Factors with Support Vector Machine.

Interdisciplinary sciences, computational life sciences Jan 29, 2018
Essential hypertension (EH) has become a major chronic disease around the world. To build a risk-predicting model for EH can help to interpose people's lifestyle and dietary habit to decrease the risk of getting EH. In this study, we constructed a EH...
(1)
Support Vector Machine Environment Essential Hypertension Humans Risk Factors ROC Curve Genetic Predisposition to Disease Models, Genetic
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An artificial nociceptor based on a diffusive memristor.

Nature communications Jan 29, 2018
A nociceptor is a critical and special receptor of a sensory neuron that is able to detect noxious stimulus and provide a rapid warning to the central nervous system to start the motor response in the human body and humanoid robotics. It differs from...
Electronics Nociceptors Receptors, Artificial Humans Artificial Intelligence Robotics Diffusion
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Automatic QRS complex detection using two-level convolutional neural network.

Biomedical engineering online Jan 29, 2018
BACKGROUND: The QRS complex is the most noticeable feature in the electrocardiogram (ECG) signal, therefore, its detection is critical for ECG signal analysis. The existing detection methods largely depend on hand-crafted manual features and paramete...
Humans Neural Networks, Computer Algorithms Signal Processing, Computer-Assisted Arrhythmias, Cardiac Signal-To-Noise Ratio Sensitivity and Specificity Models, Theoretical Electrocardiography
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Artificial intelligence on the identification of risk groups for osteoporosis, a general review.

Biomedical engineering online Jan 29, 2018
INTRODUCTION: The goal of this paper is to present a critical review on the main systems that use artificial intelligence to identify groups at risk for osteoporosis or fractures. The systems considered for this study were those that fulfilled the fo...
(1)
Osteoporosis Humans Risk Factors Artificial Intelligence Randomized Controlled Trials as Topic
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Comparing Three Data Mining Algorithms for Identifying the Associated Risk Factors of Type 2 Diabetes.

Iranian biomedical journal Jan 27, 2018
BACKGROUND: Increasing the prevalence of type 2 diabetes has given rise to a global health burden and a concern among health service providers and health administrators. The current study aimed at developing and comparing some statistical models to i...
Support Vector Machine Iran Data Mining Male Middle Aged Diabetes Mellitus, Type 2 Humans Neural Networks, Computer Algorithms Female Risk Factors Adult
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