AIMC Topic: Young Adult
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Assessment of Facial Morphologic Features in Patients With Congenital Adrenal Hyperplasia Using Deep Learning.
JAMA network open
Nov 2, 2020
IMPORTANCE: Congenital adrenal hyperplasia (CAH) is the most common primary adrenal insufficiency in children, involving excess androgens secondary to disrupted steroidogenesis as early as the seventh gestational week of life. Although structural bra...
Accurate detection of cerebellar smooth pursuit eye movement abnormalities via mobile phone video and machine learning.
Scientific reports
Oct 29, 2020
Eye movements are disrupted in many neurodegenerative diseases and are frequent and early features in conditions affecting the cerebellum. Characterizing eye movements is important for diagnosis and may be useful for tracking disease progression and ...
A Novel Method for Sleep-Stage Classification Based on Sonification of Sleep Electroencephalogram Signals Using Wavelet Transform and Recurrent Neural Network.
European neurology
Oct 29, 2020
INTRODUCTION: Visual sleep-stage scoring is a time-consuming technique that cannot extract the nonlinear characteristics of electroencephalogram (EEG). This article presents a novel method for sleep-stage differentiation based on sonification of slee...
Developing a Process for the Analysis of User Journeys and the Prediction of Dropout in Digital Health Interventions: Machine Learning Approach.
Journal of medical Internet research
Oct 28, 2020
BACKGROUND: User dropout is a widespread concern in the delivery and evaluation of digital (ie, web and mobile apps) health interventions. Researchers have yet to fully realize the potential of the large amount of data generated by these technology-b...
Designing individual-specific and trial-specific models to accurately predict the intensity of nociceptive pain from single-trial fMRI responses.
NeuroImage
Oct 27, 2020
Using machine learning to predict the intensity of pain from fMRI has attracted rapidly increasing interests. However, due to remarkable inter- and intra-individual variabilities in pain responses, the performance of existing fMRI-based pain predicti...
The use of machine learning improves the assessment of drug-induced driving behaviour.
Accident; analysis and prevention
Oct 27, 2020
RATIONALE: Car-driving performance is negatively affected by the intake of alcohol, tranquillizers, sedatives and sleep deprivation. Although several studies have shown that the standard deviation of the lateral position on the road (SDLP) is sensiti...
Discrimination of alcohol dependence based on the convolutional neural network.
PloS one
Oct 27, 2020
In this paper, a total of 20 sites of single nucleotide polymorphisms (SNPs) on the serotonin 3 receptor A gene (HTR3A) and B gene (HTR3B) are used for feature fusion with age, education and marital status information, and the grid search-support vec...
Traditional and New Methods of Bone Age Assessment-An Overview.
Journal of clinical research in pediatric endocrinology
Oct 26, 2020
Bone age is one of biological indicators of maturity used in clinical practice and it is a very important parameter of a child’s assessment, especially in paediatric endocrinology. The most widely used method of bone age assessment is by performing a...
Neural Networks, Computer
Female
Infant, Newborn
Reproducibility of Results
Young Adult
Humans
Child, Preschool
Child
Age Factors
Predictive Value of Tests
Radiographic Image Interpretation, Computer-Assisted
Male
Infant
Diagnosis, Computer-Assisted
Deep Learning
Adolescent
Age Determination by Skeleton
Adolescent Development
Hand Bones
Observer Variation
Automation
Child Development
Wrist Joint
Multi-band MR fingerprinting (MRF) ASL imaging using artificial-neural-network trained with high-fidelity experimental data.
Magnetic resonance in medicine
Oct 26, 2020
PURPOSE: We aim to leverage the power of deep-learning with high-fidelity training data to improve the reliability and processing speed of hemodynamic mapping with MR fingerprinting (MRF) arterial spin labeling (ASL).
Can artificial intelligence distinguish between malignant and benign mediastinal lymph nodes using sonographic features on EBUS images?
Current medical research and opinion
Oct 24, 2020
AIMS: This study aimed to develop a new intelligent diagnostic approach using an artificial neural network (ANN). Moreover, we investigated whether the learning-method-guided quantitative analysis approach adequately described mediastinal lymphadenop...
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