AIMC Topic: Adolescent

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Ensemble learning with 3D convolutional neural networks for functional connectome-based prediction.

NeuroImage
The specificity and sensitivity of resting state functional MRI (rs-fMRI) measurements depend on preprocessing choices, such as the parcellation scheme used to define regions of interest (ROIs). In this study, we critically evaluate the effect of bra...

Diagnostic value of spirometry vs impulse oscillometry: A comparative study in children with sickle cell disease.

Pediatric pulmonology
BACKGROUND: Spirometry is conventionally used to diagnose airway diseases in children with sickle cell disease (C-SCD). However, spirometry is difficult for younger children to perform, is effort dependent, and it provides limited information on resp...

Outcome prediction of out-of-hospital cardiac arrest with presumed cardiac aetiology using an advanced machine learning technique.

Resuscitation
BACKGROUND: Outcome prediction for patients with out-of-hospital cardiac arrest (OHCA) has the possibility to detect patients who could have been potentially saved. Advanced machine learning techniques have recently been developed and employed for cl...

Real-time estimation of electric fields induced by transcranial magnetic stimulation with deep neural networks.

Brain stimulation
BACKGROUND: Transcranial magnetic stimulation (TMS) plays an important role in treatment of mental and neurological illnesses, and neurosurgery. However, it is difficult to target specific brain regions accurately because the complex anatomy of the b...

SIMON, an Automated Machine Learning System, Reveals Immune Signatures of Influenza Vaccine Responses.

Journal of immunology (Baltimore, Md. : 1950)
Machine learning holds considerable promise for understanding complex biological processes such as vaccine responses. Capturing interindividual variability is essential to increase the statistical power necessary for building more accurate predictive...

An intelligent warning model for early prediction of cardiac arrest in sepsis patients.

Computer methods and programs in biomedicine
BACKGROUND: Sepsis-associated cardiac arrest is a common issue with the low survival rate. Early prediction of cardiac arrest can provide the time required for intervening and preventing its onset in order to reduce mortality. Several studies have be...

Using Machine Learning to Identify Suicide Risk: A Classification Tree Approach to Prospectively Identify Adolescent Suicide Attempters.

Archives of suicide research : official journal of the International Academy for Suicide Research
This study applies classification tree analysis to prospectively identify suicide attempters among a large adolescent community sample, to demonstrate the strengths and limitations of this approach for risk identification. Data were drawn from the Na...

IAPSO-AIRS: A novel improved machine learning-based system for wart disease treatment.

Journal of medical systems
Wart disease (WD) is a skin illness on the human body which is caused by the human papillomavirus (HPV). This study mainly concentrates on common and plantar warts. There are various treatment methods for this disease, including the popular immunothe...

Using heart rate profiles during sleep as a biomarker of depression.

BMC psychiatry
BACKGROUND: Abnormalities in heart rate during sleep linked to impaired neuro-cardiac modulation may provide new information about physiological sleep signatures of depression. This study assessed the validity of an algorithm using patterns of heart ...