AIMC Topic: Cross-Sectional Studies

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Validity of Robot-Based Assessments of Upper Extremity Function.

Archives of physical medicine and rehabilitation May 5, 2017
OBJECTIVE: To examine the validity of 5 robot-based assessments of arm motor function poststroke.
Humans Female Aged Aged, 80 and over Robotics Disability Evaluation Stroke Paresis Upper Extremity Young Adult Adult Cross-Sectional Studies Male Middle Aged
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Correlates of sleep quality in midlife and beyond: a machine learning analysis.

Sleep medicine Mar 27, 2017
OBJECTIVES: In older adults, traditional metrics derived from polysomnography (PSG) are not well correlated with subjective sleep quality. Little is known about whether the association between PSG and subjective sleep quality changes with age, or whe...
Male Aging Middle Aged Cohort Studies Electroencephalography Machine Learning Brain Female Cross-Sectional Studies Self Report Sleep Multivariate Analysis Independent Living Polysomnography Humans
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Longitudinal analysis of discussion topics in an online breast cancer community using convolutional neural networks.

Journal of biomedical informatics Mar 18, 2017
Identifying topics of discussions in online health communities (OHC) is critical to various information extraction applications, but can be difficult because topics of OHC content are usually heterogeneous and domain-dependent. In this paper, we prov...
Humans Neural Networks, Computer Female Breast Neoplasms Cross-Sectional Studies Internet Patient Participation
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Classification of suicide attempters in schizophrenia using sociocultural and clinical features: A machine learning approach.

General hospital psychiatry Mar 4, 2017
OBJECTIVE: Suicide is a major concern for those afflicted by schizophrenia. Identifying patients at the highest risk for future suicide attempts remains a complex problem for psychiatric interventions. Machine learning models allow for the integratio...
Female Risk Factors Adult Cross-Sectional Studies Male Middle Aged Suicide, Attempted Models, Statistical Humans Schizophrenia Machine Learning
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Phenomapping for the Identification of Hypertensive Patients with the Myocardial Substrate for Heart Failure with Preserved Ejection Fraction.

Journal of cardiovascular translational research Mar 3, 2017
We sought to evaluate whether unbiased machine learning of dense phenotypic data ("phenomapping") could identify distinct hypertension subgroups that are associated with the myocardial substrate (i.e., abnormal cardiac mechanics) for heart failure wi...
Echocardiography, Doppler Predictive Value of Tests Blood Pressure Heart Failure Pattern Recognition, Automated Stress, Mechanical Adult Phenotype Middle Aged Cross-Sectional Studies Humans Prognosis Risk Assessment Biomechanical Phenomena Female United States Machine Learning Risk Factors Male Hypertension Stroke Volume Aged Cluster Analysis
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Genetic Variation in CD36 Is Associated with Decreased Fat and Sugar Intake in Obese Children and Adolescents.

Journal of nutrigenetics and nutrigenomics Feb 25, 2017
BACKGROUND/AIMS: Taste is recognized as an important predictor of food choices. Thus, polymorphisms in genes encoding taste receptors may explain the variability in food preference and intake. Here, we aimed to determine whether genetic variation in ...
CD36 Antigens Taste Perception Female Dietary Fats Risk Factors Dietary Sugars Humans Genetic Association Studies Adolescent Cross-Sectional Studies Pediatric Obesity Child Male Eating Brazil Genetic Predisposition to Disease Food Preferences Polymorphism, Single Nucleotide Feeding Behavior Genotype
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Monitoring Hitting Load in Tennis Using Inertial Sensors and Machine Learning.

International journal of sports physiology and performance Feb 9, 2017
CONTEXT: Quantifying external workload is fundamental to training prescription in sport. In tennis, global positioning data are imprecise and fail to capture hitting loads. The current gold standard (manual notation) is time intensive and often not p...
Athletic Performance Video Recording Tennis Biomechanical Phenomena Male Adolescent Wearable Electronic Devices Humans Machine Learning Female Young Adult Cross-Sectional Studies
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Robot-aided developmental assessment of wrist proprioception in children.

Journal of neuroengineering and rehabilitation Jan 9, 2017
BACKGROUND: Several neurodevelopmental disorders and brain injuries in children have been associated with proprioceptive dysfunction that will negatively affect their movement. Unfortunately, there is lack of reliable and objective clinical examinati...
Child Robotics Movement Proprioception Wrist Joint Female Humans Young Adult Cross-Sectional Studies Male Adolescent
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High Amounts of Sitting, Low Cardiorespiratory Fitness, and Low Physical Activity Levels: 3 Key Ingredients in the Recipe for Influencing Metabolic Syndrome Prevalence.

American journal of health promotion : AJHP Dec 22, 2016
PURPOSE: Limited research has evaluated the independent and additive associations of moderate-to-vigorous physical activity (MVPA), sedentary behavior (SB), and cardiorespiratory fitness (CRF) with metabolic syndrome, which was the purpose of this st...
Blood Glucose Logistic Models Accelerometry Nutrition Surveys Cross-Sectional Studies Humans Blood Pressure Male Metabolic Syndrome Sedentary Behavior Female Oxygen Consumption Middle Aged Lipids Sitting Position Exercise Young Adult Exercise Test Prevalence Adult Adiposity Cardiorespiratory Fitness
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Motivation, expectations, and usability of a driven gait orthosis in stroke patients and their therapists.

Topics in stroke rehabilitation Dec 20, 2016
BACKGROUND: In the development of efficacious driven gait orthoses (DGO), it is an added value to consider patients' and therapists' perspectives concerning robot-assisted gait training (RAGT). A better understanding of these issues may improve the p...
Cross-Sectional Studies Male Middle Aged Robotics Stroke Exercise Therapy Motivation Therapy, Computer-Assisted Orthotic Devices Patient Preference Humans Female Aged Aged, 80 and over Adult Stroke Rehabilitation Patient Acceptance of Health Care Gait Disorders, Neurologic Physical Therapists
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