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Personality traits as predictors of depression across the lifespan.
Journal of affective disorders
Mar 26, 2024
BACKGROUND: Depression is a major public health concern. A barrier for research has been the heterogeneous nature of depression, complicated by the categorical diagnosis of depression which is based on a cluster of symptoms, each with its own etiolog...
Machine learning-based prediction of tear osmolarity for contact lens practice.
Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists)
Mar 25, 2024
PURPOSE: This study addressed the utilisation of machine learning techniques to estimate tear osmolarity, a clinically significant yet challenging parameter to measure accurately. Elevated tear osmolarity has been observed in contact lens wearers and...
Applying Common Spatial Pattern and Convolutional Neural Network to Classify Movements via EEG Signals.
Clinical EEG and neuroscience
Mar 24, 2024
Developing an electroencephalography (EEG)-based brain-computer interface (BCI) system is crucial to enhancing the control of external prostheses by accurately distinguishing various movements through brain signals. This innovation can provide comfor...
Frontal facial analysis of female celebrity attractiveness standards through artificial intelligence.
Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery
Mar 24, 2024
The contemporary significance of celebrities' facial aesthetics underscores their heightened importance in shaping attractiveness standards. This retrospective study aimed to investigate the impact of patterns on aesthetic canons in the profile views...
Enhancing Patient Safety in Prehospital Environment: Analyzing Patient Perspectives on Non-Transport Decisions With Natural Language Processing and Machine Learning.
Journal of patient safety
Mar 23, 2024
OBJECTIVE: This research explored the experiences and perspectives of patients declining hospital transportation after receiving prehospital emergency care using advanced computational techniques.
Deep Learning Accelerated Brain Diffusion-Weighted MRI with Super Resolution Processing.
Academic radiology
Mar 22, 2024
OBJECTIVES: To investigate the clinical feasibility and image quality of accelerated brain diffusion-weighted imaging (DWI) with deep learning image reconstruction and super resolution.
Using multivariate pattern analysis to increase effect sizes for event-related potential analyses.
Psychophysiology
Mar 22, 2024
Multivariate pattern analysis (MVPA) approaches can be applied to the topographic distribution of event-related potential (ERP) signals to "decode" subtly different stimulus classes, such as different faces or different orientations. These approaches...
A motion-corrected deep-learning reconstruction framework for accelerating whole-heart magnetic resonance imaging in patients with congenital heart disease.
Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
Mar 22, 2024
BACKGROUND: Cardiovascular magnetic resonance (CMR) is an important imaging modality for the assessment and management of adult patients with congenital heart disease (CHD). However, conventional techniques for three-dimensional (3D) whole-heart acqu...
Identification and prediction of association patterns between nutrient intake and anemia using machine learning techniques: results from a cross-sectional study with university female students from Palestine.
European journal of nutrition
Mar 21, 2024
PURPOSE: This study utilized data mining and machine learning (ML) techniques to identify new patterns and classifications of the associations between nutrient intake and anemia among university students.
Transcranial Magnetic Stimulation-Based Machine Learning Prediction of Tumor Grading in Motor-Eloquent Gliomas.
Neurosurgery
Mar 21, 2024
BACKGROUND: Navigated transcranial magnetic stimulation (nTMS) is a well-established preoperative mapping tool for motor-eloquent glioma surgery. Machine learning (ML) and nTMS may improve clinical outcome prediction and histological correlation.
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