AIMC Topic: Young Adult
Clear Filters Showing 2251 to 2260 of 4556 articles
Transthoracic echocardiography monitoring during ASD closure using an artificial hand system.
Cardiovascular ultrasound
Jun 17, 2020
AIM: Continuous real-time echocardiographic monitoring is essential for guidance during ASD closure. However, transthoracic echocardiography (TTE) can only be implemented intermittently during fluoroscopy. We evaluate a novel approach to provide real...
Decoding attention control and selection in visual spatial attention.
Human brain mapping
Jun 16, 2020
Event-related potentials (ERPs) are used extensively to investigate the neural mechanisms of attention control and selection. The univariate ERP approach, however, has left important questions inadequately answered. We addressed two questions by appl...
Improving blood glucose level predictability using machine learning.
Diabetes/metabolism research and reviews
Jun 14, 2020
This study was designed to improve blood glucose level predictability and future hypoglycemic and hyperglycemic event alerts through a novel patient-specific supervised-machine-learning (SML) analysis of glucose level based on a continuous-glucose-mo...
Comparison of Machine Learning Methods and Conventional Logistic Regressions for Predicting Gestational Diabetes Using Routine Clinical Data: A Retrospective Cohort Study.
Journal of diabetes research
Jun 12, 2020
BACKGROUND: Gestational diabetes mellitus (GDM) contributes to adverse pregnancy and birth outcomes. In recent decades, extensive research has been devoted to the early prediction of GDM by various methods. Machine learning methods are flexible predi...
Logistic Models
Reproducibility of Results
Humans
Routinely Collected Health Data
Decision Trees
Young Adult
Machine Learning
Glycated Hemoglobin
Adult
Retrospective Studies
Cholesterol
Blood Glucose
Pregnancy
Uric Acid
Cohort Studies
Female
Diabetes, Gestational
Lipoproteins, HDL
Maternal Age
Triglycerides
Clinical Decision Rules
Pregnancy in Obesity
Differentiating molecular etiologies of Angelman syndrome through facial phenotyping using deep learning.
American journal of medical genetics. Part A
Jun 11, 2020
Angelman syndrome (AS) is caused by several genetic mechanisms that impair the expression of maternally-inherited UBE3A through deletions, paternal uniparental disomy (UPD), UBE3A pathogenic variants, or imprinting defects. Current methods of differe...
Binary CorNET: Accelerator for HR Estimation From Wrist-PPG.
IEEE transactions on biomedical circuits and systems
Jun 11, 2020
Research on heart rate (HR) estimation using wrist-worn photoplethysmography (PPG) sensors have progressed rapidly owing to the prominence of commercial sensing modules, used widely for lifestyle monitoring. Reported methodologies have been fairly su...
Age-Related Differences in the Uncanny Valley Effect.
Gerontology
Jun 11, 2020
BACKGROUND: Due to declining birthrates and an increasing aging population, shortage of the caregiving labor force has become a global issue. Among various efforts toward the solution, introducing robotic products for assistance could provide an effe...
Prospective, comparative evaluation of a deep neural network and dermoscopy in the diagnosis of onychomycosis.
PloS one
Jun 11, 2020
BACKGROUND: Onychomycosis is the most common nail disorder and is associated with diagnostic challenges. Emerging non-invasive, real-time techniques such as dermoscopy and deep convolutional neural networks have been proposed for the diagnosis of thi...
Hydroxides
Potassium Compounds
Mycological Typing Techniques
Photography
Foot Dermatoses
Onychomycosis
Diagnosis, Computer-Assisted
Deep Learning
Computer Systems
Predictive Value of Tests
Dermatologists
Young Adult
Adult
Humans
Diagnostic Errors
Neural Networks, Computer
Male
Algorithms
Middle Aged
Prospective Studies
Female
Dermoscopy
Deep learning for EEG-based Motor Imagery classification: Accuracy-cost trade-off.
PloS one
Jun 11, 2020
Electroencephalography (EEG) datasets are often small and high dimensional, owing to cumbersome recording processes. In these conditions, powerful machine learning techniques are essential to deal with the large amount of information and overcome the...
Machine-learning-based diagnostics of EEG pathology.
NeuroImage
Jun 10, 2020
Machine learning (ML) methods have the potential to automate clinical EEG analysis. They can be categorized into feature-based (with handcrafted features), and end-to-end approaches (with learned features). Previous studies on EEG pathology decoding ...
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30619
- Neural Networks, Computer 29506
- Algorithms 26548
- Deep Learning 26025
- Artificial Intelligence 24055
- Robotics 13286
- Image Processing, Computer-Assisted 9387
- Retrospective Studies 8943
- Magnetic Resonance Imaging 6074
- Reproducibility of Results 5540
- Tomography, X-Ray Computed 4682
- Support Vector Machine 4644
- Computational Biology 4191
- Brain 3993
- Computer Simulation 3858
Recent Journals
- Scientific reports 5371
- Sensors (Basel, Switzerland) 4794
- PloS one 3990
- Neural networks : the official journal of the International Neural Network Society 2927
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1122
- Journal of chemical information and modeling 987
- Nature communications 889
- Computer methods and programs in biomedicine 863
- Bioinformatics (Oxford, England) 859
- Briefings in bioinformatics 849
- IEEE transactions on neural networks and learning systems 822