AIMC Topic: Young Adult

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Predicting changes of incisor and facial profile following orthodontic treatment: a machine learning approach.

Head & face medicine
BACKGROUND: Facial aesthetics is one of major motivations for seeking orthodontic treatment. However, even for experienced professionals, the impact and extent of incisor and soft tissue changes remain largely empirical. With the application of inter...

Identification of testicular cancer with T2-weighted MRI-based radiomics and automatic machine learning.

BMC cancer
BACKGROUND: Distinguishing between benign and malignant testicular lesions on clinical magnetic resonance imaging (MRI) is crucial for guiding treatment planning. However, conventional MRI-based radiomics to identify testicular cancer requires expert...

A large-scale multicenter study of reference intervals and clinical potential for homocysteine-folate cycle metabolites in Northern Chinese population.

Clinica chimica acta; international journal of clinical chemistry
OBJECTIVES: The study was conducted to establish the reference intervals of homocysteine-folate cycle metabolites based on the healthy population from multiple centers in northern China, and determine their clinical significance in the diagnosis of r...

Exploring the factors influencing the adoption of artificial intelligence technology by university teachers: the mediating role of confidence and AI readiness.

BMC psychology
OBJECTIVES: This study aims to explore the mediating role of confidence and artificial intelligence (AI) readiness in university teachers' behavioral intention to adopt AI technology, providing empirical support for enhancing teachers' willingness to...

Machine learning combined with infrared spectroscopy for detection of hypertension pregnancy: towards newborn and pregnant blood analysis.

BMC pregnancy and childbirth
Biochemical changes in the cervix during labor are not well understood. This gap in knowledge is significant, as understanding the precise biochemical processes can provide critical insights into the mechanisms of labor and potentially inform better ...

Deep learning-based reconstruction for three-dimensional volumetric brain MRI: a qualitative and quantitative assessment.

BMC medical imaging
BACKGROUND: To evaluate the performance of a deep learning reconstruction (DLR) based on Adaptive-Compressed sensing (CS)-Network for brain MRI and validate it in a clinical setting.

Recurrent and convolutional neural networks in classification of EEG signal for guided imagery and mental workload detection.

Scientific reports
The Guided Imagery technique is reported to be used by therapists all over the world in order to increase the comfort of patients suffering from a variety of disorders from mental to oncology ones and proved to be successful in numerous of ways. Poss...

Machine learning algorithms to predict khat chewing practice and its predictors among men aged 15 to 59 in Ethiopia: further analysis of the 2011 and 2016 Ethiopian Demographic and Health Survey.

Frontiers in public health
INTRODUCTION: Khat chewing is a significant public health issue in Ethiopia, influenced by various demographic factors. Understanding the prevalence and determinants of khat chewing practices is essential to developing targeted interventions. Therefo...

Predicting high anger intensity using ecological momentary assessment and wearable-derived physiological data in a trauma-affected sample.

European journal of psychotraumatology
Digital technologies offer tremendous potential to predict dysregulated mood and behavior within an individual's environment, and in doing so can support the development of new digital health interventions. However, no prediction models have been bu...

Monocyte distribution width (MDW) as a reliable diagnostic biomarker for sepsis in patients with HIV.

Emerging microbes & infections
Sepsis is a leading cause of death among patients with HIV, but early diagnosis remains a challenge. This study evaluates the diagnostic performance of monocyte distribution width (MDW) in detecting sepsis in patients with HIV. A prospective observat...