AIMC Topic: Adolescent

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A Machine Learning Model for Evaluating Imported Disease Screening Strategies in Immigrant Populations.

The American journal of tropical medicine and hygiene
Given the high prevalence of imported diseases in immigrant populations, it has postulated the need to establish screening programs that allow their early diagnosis and treatment. We present a mathematical model based on machine learning methodologie...

Multi-step validation of a deep learning-based system for the quantification of bowel preparation: a prospective, observational study.

The Lancet. Digital health
BACKGROUND: Inadequate bowel preparation is associated with a decrease in adenoma detection rate (ADR). A deep learning-based bowel preparation assessment system based on the Boston bowel preparation scale (BBPS) has been previously established to ca...

Deep Learning for Identification of Alcohol-Related Content on Social Media (Reddit and Twitter): Exploratory Analysis of Alcohol-Related Outcomes.

Journal of medical Internet research
BACKGROUND: Many social media studies have explored the ability of thematic structures, such as hashtags and subreddits, to identify information related to a wide variety of mental health disorders. However, studies and models trained on specific the...

Tooth and Bone Parameters in the Assessment of the Chronological Age of Children and Adolescents Using Neural Modelling Methods.

Sensors (Basel, Switzerland)
The analog methods used in the clinical assessment of the patient's chronological age are subjective and characterized by low accuracy. When using those methods, there is a noticeable discrepancy between the chronological age and the age estimated ba...

Acceptability, usefulness, and satisfaction with a web-based video-tailored physical activity intervention: The TaylorActive randomized controlled trial.

Journal of sport and health science
PURPOSE: This study aimed to examine the usage, acceptability, usability, perceived usefulness, and satisfaction of a web-based video-tailored physical activity (PA) intervention (TaylorActive) in adults.

MRI-Based Machine Learning Prediction Framework to Lateralize Hippocampal Sclerosis in Patients With Temporal Lobe Epilepsy.

Neurology
BACKGROUND AND OBJECTIVES: MRI fails to reveal hippocampal pathology in 30% to 50% of temporal lobe epilepsy (TLE) surgical candidates. To address this clinical challenge, we developed an automated MRI-based classifier that lateralizes the side of co...

Efficacy of a comprehensive binary classification model using a deep convolutional neural network for wireless capsule endoscopy.

Scientific reports
The manual reading of capsule endoscopy (CE) videos in small bowel disease diagnosis is time-intensive. Algorithms introduced to automate this process are premature for real clinical applications, and multi-diagnosis using these methods has not been ...

Deep learning analysis and age prediction from shoeprints.

Forensic science international
Human gaits are the patterns of limb movements which involve both the upper and lower body parts. These patterns in terms of step rate, gait speed, stance widening, stride, and bipedal forces are influenced by different factors including environmenta...

Machine learning models of ischemia/hemorrhage in moyamoya disease and analysis of its risk factors.

Clinical neurology and neurosurgery
OBJECT: This study aimed to determine the risk factors of ischemic/hemorrhagic stroke in patients suffering moyamoya disease (MMD), as well as to compare the effects of six analysis methods.