AIMC Topic: Adolescent

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Mobile detection of autism through machine learning on home video: A development and prospective validation study.

PLoS medicine
BACKGROUND: The standard approaches to diagnosing autism spectrum disorder (ASD) evaluate between 20 and 100 behaviors and take several hours to complete. This has in part contributed to long wait times for a diagnosis and subsequent delays in access...

Refining Convolutional Neural Network Detection of Small-Bowel Obstruction in Conventional Radiography.

AJR. American journal of roentgenology
OBJECTIVE: The purpose of this study was to evaluate improvement of convolutional neural network detection of high-grade small-bowel obstruction on conventional radiographs with increased training set size.

Individual differences in rate of acquiring stable neural representations of tasks in fMRI.

PloS one
Task-related functional magnetic resonance imaging (fMRI) is a widely-used tool for studying the neural processing correlates of human behavior in both healthy and clinical populations. There is growing interest in mapping individual differences in f...

Cocoa flavanol effects on markers of oxidative stress and recovery after muscle damage protocol in elite rugby players.

Nutrition (Burbank, Los Angeles County, Calif.)
OBJECTIVES: Strenuous exercise can impair athletic performance due to muscular inflammation and oxidative stress. Antioxidants such as cocoa flavanols have been used as a supplement to prevent oxidative stress; however, the benefits of dietary antiox...

Supervised machine learning to decipher the complex associations between neuro-immune biomarkers and quality of life in schizophrenia.

Metabolic brain disease
Stable phase schizophrenia is characterized by altered patterning in tryptophan catabolites (TRYCATs) and memory impairments, which are associated with PHEMN (psychosis, hostility, excitation, mannerism and negative) and DAPS (depression, anxiety and...

Machine learning approaches for predicting high cost high need patient expenditures in health care.

Biomedical engineering online
BACKGROUND: This paper studies the temporal consistency of health care expenditures in a large state Medicaid program. Predictive machine learning models were used to forecast the expenditures, especially for the high-cost, high-need (HCHN) patients.