AIMC Topic: Young Adult

Clear Filters Showing 1701 to 1710 of 5268 articles

Estimating the Severity of Obstructive Sleep Apnea Using ECG, Respiratory Effort and Neural Networks.

IEEE journal of biomedical and health informatics
OBJECTIVE: wearable sensor technology has progressed significantly in the last decade, but its clinical usability for the assessment of obstructive sleep apnea (OSA) is limited by the lack of large and representative datasets simultaneously acquired ...

Knowledge and attitudes toward artificial intelligence in nursing among various categories of professionals in China: a cross-sectional study.

Frontiers in public health
OBJECTIVES: The application of artificial intelligence (AI) in healthcare is an important public health issue. However, few studies have investigated the perceptions and attitudes of healthcare professionals toward its applications in nursing. This s...

Do all sedatives promote biological sleep electroencephalogram patterns? A machine learning framework to identify biological sleep promoting sedatives using electroencephalogram.

PloS one
BACKGROUND: Sedatives are commonly used to promote sleep in intensive care unit patients. However, it is not clear whether sedation-induced states are similar to the biological sleep. We explored if sedative-induced states resemble biological sleep u...

Predicting efficacy of antiseizure medication treatment with machine learning algorithms in North Indian population.

Epilepsy research
PURPOSE: This study aimed to develop a classifier using supervised machine learning to effectively assess the impact of clinical, demographical, and biochemical factors in accurately predicting the antiseizure medications (ASMs) treatment response in...

Machine learning methods in automated detection of CT enterography findings in Crohn's disease: A feasibility study.

Clinical imaging
PURPOSE: Qualitative findings in Crohn's disease (CD) can be challenging to reliably report and quantify. We evaluated machine learning methodologies to both standardize the detection of common qualitative findings of ileal CD and determine finding s...

Validating the AI-assisted second language (L2) learning attitude scale for Chinese college students and its correlation with L2 proficiency.

Acta psychologica
The positive impact of Artificial Intelligence (AI) on second language (L2) learning is well-documented. An individual's attitude toward AI significantly influences its adoption. Despite this, no specific scale has been designed to measure this attit...

Personalized Language Model Selection Through Gamified Elicitation of Contrastive Concept Preferences.

IEEE transactions on visualization and computer graphics
Language models are widely used for different Natural Language Processing tasks while suffering from a lack of personalization. Personalization can be achieved by, e.g., fine-tuning the model on training data that is created by the user (e.g., social...

Development of an Automated Free Flap Monitoring System Based on Artificial Intelligence.

JAMA network open
IMPORTANCE: Meticulous postoperative flap monitoring is essential for preventing flap failure and achieving optimal results in free flap operations, for which physical examination has remained the criterion standard. Despite the high reliability of p...

Identifying subgroups of urge suppression in Obsessive-Compulsive Disorder using machine learning.

Journal of psychiatric research
Obsessive-compulsive disorder (OCD) is phenomenologically heterogeneous. While predominant models suggest fear and harm prevention drive compulsions, many patients also experience uncomfortable sensory-based urges ("sensory phenomena") that may be as...

Caries lesions diagnosis with deep convolutional neural network in intraoral QLF images by handheld device.

BMC oral health
OBJECTIVES: This study investigated the effectiveness of a deep convolutional neural network (CNN) in diagnosing and staging caries lesions in quantitative light-induced fluorescence (QLF) images taken by a self-manufactured handheld device.