AIMC Topic: Adolescent

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Machine Learning Models for Analysis of Vital Signs Dynamics: A Case for Sepsis Onset Prediction.

Journal of healthcare engineering
OBJECTIVE: Achieving accurate prediction of sepsis detection moment based on bedside monitor data in the intensive care unit (ICU). A good clinical outcome is more probable when onset is suspected and treated on time, thus early insight of sepsis ons...

Machine-learned analysis of side-differences in odor identification performance.

Neuroscience
A right-left dichotomy of olfactory processes has been recognized on several levels of the perception or processing of olfactory input. On a clinical level, the lateralization of components of human olfaction is contrasted by the predominantly birhin...

Machine-learning-derived rules set excludes risk of Parkinson's disease in patients with olfactory or gustatory symptoms with high accuracy.

Journal of neurology
BACKGROUND: Chemosensory loss is a symptom of Parkinson's disease starting already at preclinical stages. Their appearance without an identifiable etiology therefore indicates a possible early symptom of Parkinson's disease. Supervised machine-learni...

A Gradient Boosting Machine Learning Model for Predicting Early Mortality in the Emergency Department Triage: Devising a Nine-Point Triage Score.

Journal of general internal medicine
BACKGROUND: Emergency departments (ED) are becoming increasingly overwhelmed, increasing poor outcomes. Triage scores aim to optimize the waiting time and prioritize the resource usage. Artificial intelligence (AI) algorithms offer advantages for cre...

Single-slice Alzheimer's disease classification and disease regional analysis with Supervised Switching Autoencoders.

Computers in biology and medicine
BACKGROUND: Alzheimer's disease (AD) is a difficult to diagnose pathology of the brain that progressively impairs cognitive functions. Computer-assisted diagnosis of AD based on image analysis is an emerging tool to support AD diagnosis. In this arti...

Comparison of Bagging and Boosting Ensemble Machine Learning Methods for Automated EMG Signal Classification.

BioMed research international
The neuromuscular disorders are diagnosed using electromyographic (EMG) signals. Machine learning algorithms are employed as a decision support system to diagnose neuromuscular disorders. This paper compares bagging and boosting ensemble learning met...

Qualitative, Exploratory, and Multidimensional Study of Telepresence Robots for Overcoming Social Isolation of Children and Adolescents Hospitalized in Onco-Hematology.

Journal of adolescent and young adult oncology
Treatment of pediatric cancers and hematological malignancies requires long periods of isolation in a sterile room. To promote family connections, telepresence robots have been made available in the homes of hospitalized patients. Our aim was to eva...

A vision-based approach for fall detection using multiple cameras and convolutional neural networks: A case study using the UP-Fall detection dataset.

Computers in biology and medicine
The automatic recognition of human falls is currently an important topic of research for the computer vision and artificial intelligence communities. In image analysis, it is common to use a vision-based approach for fall detection and classification...

Machine learning techniques to predict the effectiveness of music therapy: A randomized controlled trial.

Computer methods and programs in biomedicine
BACKGROUND: The literature shows the effectiveness of music listening, but which factors and what types of music produce therapeutic effects, as well as how music therapists can select music, remain unclear. Here, we present a study to establish the ...