AIMC Topic: Young Adult

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Alendronate/Vitamin D for attenuating bone mineral density loss during antiretroviral initiation: a pilot randomized controlled trial.

HIV research & clinical practice Feb 27, 2020
Antiretroviral therapy (ART) initiation is associated with decreases in bone mineral density (BMD). To plan for a larger trial, we sought to obtain preliminary estimates for the difference in the change in BMD at 48 weeks achieved with 24 weeks of p...
Male Humans CD4 Lymphocyte Count Pilot Projects Bone Density HIV Infections Female Anti-Retroviral Agents Canada Alendronate Young Adult Vitamin D Bone Density Conservation Agents Adult
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Glucose outcomes of a learning-type artificial pancreas with an unannounced meal in type 1 diabetes.

Computer methods and programs in biomedicine Feb 26, 2020
BACKGROUND AND OBJECTIVES: Glycemic control with unannounced meals is the major challenge for artificial pancreas. In this study, we described the performance and safety of learning-type model predictive control (L-MPC) for artificial pancreas challe...
Diabetes Mellitus, Type 1 Outcome Assessment, Health Care Meals Insulin Infusion Systems Pancreas, Artificial Adult Humans Male Middle Aged Machine Learning Adolescent Algorithms Blood Glucose Female Aged Young Adult
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A proof of concept machine learning analysis using multimodal neuroimaging and neurocognitive measures as predictive biomarker in bipolar disorder.

Asian journal of psychiatry Feb 26, 2020
BACKGROUND: Concomitant use of complementary, multimodal imaging measures and neurocognitive measures is reported to have higher accuracy as a biomarker in Alzheimer's dementia. However, such an approach has not been examined to differentiate healthy...
Reproducibility of Results Young Adult Sensitivity and Specificity Male Psychiatric Status Rating Scales Bipolar Disorder Support Vector Machine Magnetic Resonance Imaging Neuroimaging Proof of Concept Study Humans Machine Learning Biomarkers Brain Executive Function Female
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Auto detecting deliveries in elite cricket fast bowlers using microsensors and machine learning.

Journal of sports sciences Feb 26, 2020
Cricket fast bowlers are at a high risk of injury occurrence, which has previously been shown to be correlated to bowling workloads. This study aimed to develop and test an algorithm that can automatically, reliably and accurately detect bowling deli...
Geographic Information Systems Adolescent Wearable Electronic Devices Athletic Performance Accelerometry Motor Skills Cricket Sport Humans Adult Machine Learning Cross-Sectional Studies Algorithms Biomechanical Phenomena Young Adult Male Risk Assessment
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Harnessing Population Pedigree Data and Machine Learning Methods to Identify Patterns of Familial Bladder Cancer Risk.

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology Feb 25, 2020
BACKGROUND: Relatives of patients with bladder cancer have been shown to be at increased risk for kidney, lung, thyroid, and cervical cancer after correcting for smoking-related behaviors that may concentrate in some families. We demonstrate a novel ...
Incidence Genetic Predisposition to Disease Urinary Bladder Neoplasms Data Mining Data Collection Genetic Heterogeneity Utah Pedigree Neoplastic Syndromes, Hereditary Adult Male Middle Aged Risk Assessment Adolescent Female Risk Factors Aged Aged, 80 and over Humans Young Adult Machine Learning Databases, Factual
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Artificial neural networks for predicting social comparison effects among female Instagram users.

PloS one Feb 25, 2020
Systematic exposure to social media causes social comparisons, especially among women who compare their image to others; they are particularly vulnerable to mood decrease, self-objectification, body concerns, and lower perception of themselves. This ...
Social Media Self Concept Social Behavior Social Networking Humans Poland Artificial Intelligence Anxiety Female Depression Young Adult Surveys and Questionnaires Adult Adolescent Middle Aged
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Macular Ganglion Cell-Inner Plexiform Layer Thickness Prediction from Red-free Fundus Photography using Hybrid Deep Learning Model.

Scientific reports Feb 24, 2020
We developed a hybrid deep learning model (HDLM) algorithm that quantitatively predicts macular ganglion cell-inner plexiform layer (mGCIPL) thickness from red-free retinal nerve fiber layer photographs (RNFLPs). A total of 789 pairs of RNFLPs and sp...
Aged, 80 and over Young Adult Adult Sensitivity and Specificity Intraocular Pressure Glaucoma Algorithms Retrospective Studies Female Aged ROC Curve Support Vector Machine Regression Analysis Optic Nerve Tomography, Optical Coherence Male Middle Aged Case-Control Studies Diagnosis, Computer-Assisted Deep Learning Humans Fundus Oculi Translational Research, Biomedical Retinal Ganglion Cells Diagnostic Techniques, Ophthalmological Refractometry
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Machine Learning Analysis for Quantitative Discrimination of Dried Blood Droplets.

Scientific reports Feb 24, 2020
One of the most interesting and everyday natural phenomenon is the formation of different patterns after the evaporation of liquid droplets on a solid surface. The analysis of dried patterns from blood droplets has recently gained a lot of attention,...
Exercise Image Processing, Computer-Assisted Principal Component Analysis Humans Discriminant Analysis Machine Learning Dried Blood Spot Testing Blood Chemical Analysis Algorithms Young Adult Male
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Effects of Deep Learning Reconstruction Technique in High-Resolution Non-contrast Magnetic Resonance Coronary Angiography at a 3-Tesla Machine.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes Feb 19, 2020
PURPOSE: To evaluate the effects of deep learning reconstruction (DLR) in qualitative and quantitative image quality of non-contrast magnetic resonance coronary angiography (MRCA).
Reference Values Coronary Vessels Magnetic Resonance Angiography Male Humans Middle Aged Deep Learning Female Image Processing, Computer-Assisted Young Adult Coronary Angiography Adult
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fNIRS-GANs: data augmentation using generative adversarial networks for classifying motor tasks from functional near-infrared spectroscopy.

Journal of neural engineering Feb 19, 2020
OBJECTIVE: Functional near-infrared spectroscopy (fNIRS) is expected to be applied to brain-computer interface (BCI) technologies. Since lengthy fNIRS measurements are uncomfortable for participants, it is difficult to obtain enough data to train cla...
Humans Neural Networks, Computer Support Vector Machine Psychomotor Performance Brain-Computer Interfaces Movement Motor Cortex Female Young Adult Adult Male Spectroscopy, Near-Infrared
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