AIMC Topic: Young Adult

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Using graph machine learning to identify functioning in patients with low back pain in terms of ICF.

Scientific reports
As a comprehensive perspective on functioning is useful in patient assessments, the WHO developed the International Classification of Functioning, Disability, and Health (ICF) to provide a standardized terminology and framework for describing and cla...

Recognition of anxiety and depression using gait data recorded by the kinect sensor: a machine learning approach with data augmentation.

Scientific reports
Anxiety and depression disorders are increasingly common, necessitating methods for real-time assessment and early identification. This study investigates gait analysis as a potential indicator of mental health, using the Microsoft Kinect sensor to c...

Exploring the link between the ZJU index and sarcopenia in adults aged 20-59 using NHANES and machine learning.

Scientific reports
Sarcopenia, characterized by progressive loss of muscle mass and function, is a growing public health concern. The ZJU index, a novel metabolic marker, integrates lipid metabolism and glucose regulation parameters. While its association with metaboli...

The General Attitudes towards Artificial Intelligence Scale (GAAIS): validation and psychometric properties analysis in the Italian context.

BMC psychology
This two-study investigation aimed to assess the psychometric properties of the Italian version of the General Attitudes towards Artificial Intelligence Scale (GAAIS). In study 1 (N = 236 adults) confirmatory factor analysis (CFA) was conducted to ex...

Deep learning-based automated classification of choroidal layers in en face swept-source optical coherence tomography images.

BMC ophthalmology
BACKGROUND: This study aims to develop a deep learning-based algorithm dedicated to the automated classification of choroidal layers in en face swept-source optical coherence tomography (SS-OCT) images of the eye.

Accelerating brain T2-weighted imaging using artificial intelligence-assisted compressed sensing combined with deep learning-based reconstruction: a feasibility study at 5.0T MRI.

BMC medical imaging
BACKGROUND: T2-weighted imaging (T2WI), renowned for its sensitivity to edema and lesions, faces clinical limitations due to prolonged scanning time, increasing patient discomfort, and motion artifacts. The individual applications of artificial intel...

EEG based real time classification of consecutive two eye blinks for brain computer interface applications.

Scientific reports
Human eye blinks are considered a significant contaminant or artifact in electroencephalogram (EEG), which impacts EEG-based medical or scientific applications. However, eye blink detection can instead be transformed into a potential application of b...

Evaluation of MRI-based synthetic CT for lumbar degenerative disease: a comparison with CT.

Scientific reports
Patients with lumbar degenerative disease typically undergo preoperative MRI combined with CT scans, but this approach introduces additional ionizing radiation and examination costs. To compare the effectiveness of MRI-based synthetic CT (sCT) in dis...

AI-based CT assessment of 3117 vertebrae reveals significant sex-specific vertebral height differences.

Scientific reports
Predicting vertebral height is complex due to individual factors. AI-based medical imaging analysis offers new opportunities for vertebral assessment. Thereby, these novel methods may contribute to sex-adapted nomograms and vertebral height predictio...