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Smartphone eye-tracking with deep learning: Data quality and field testing.
Behavior research methods
Jun 18, 2025
Eye-tracking is widely used to measure human attention in research, commercial, and clinical applications. With the rapid advancements in artificial intelligence and mobile computing, deep learning algorithms for computer vision-based eye tracking ha...
Understanding and acceptance of open, laparoscopic, and robotic surgery among nursing students: implications for educational curricula based on a mixed-methods study.
Journal of robotic surgery
Jun 18, 2025
This study aimed to assess university nursing students' knowledge and perceptions of open, laparoscopic, and robotic surgery applications. A simultaneous sequential nested quantitative-qualitative hybrid research method design was conducted. The sub-...
Changes in Epidemiological Characteristics of Varicella and Breakthrough Cases in Ningbo, China, From 2010 to 2023: Surveillance Study.
JMIR public health and surveillance
Jun 18, 2025
BACKGROUND: Varicella is a prevalent respiratory infectious disease. Continuous monitoring is essential to understand evolving epidemiological patterns, particularly given the impact of vaccination and recent nonpharmacological interventions.
Impact of AI-Assisted Diagnosis on American Patients' Trust in and Intention to Seek Help From Health Care Professionals: Randomized, Web-Based Survey Experiment.
Journal of medical Internet research
Jun 18, 2025
BACKGROUND: Artificial intelligence (AI) technologies are increasingly integrated into medical practice, with AI-assisted diagnosis showing promise. However, patient acceptance of AI-assisted diagnosis, compared with human-only procedures, remains un...
Test-retest reliability of kinematic and EEG low-beta spectral features in a robot-based arm movement task.
Biomedical physics & engineering express
Jun 18, 2025
Low-beta (L, 13-20 Hz) power plays a key role in upper-limb motor control and afferent processing, making it a strong candidate for a neurophysiological biomarker. We investigate the test-retest reliability of Lpower and kinematic features from a rob...
Aphasia severity prediction using a multi-modal machine learning approach.
NeuroImage
Jun 17, 2025
The present study examined an integrated multiple neuroimaging modality (T1 structural, Diffusion Tensor Imaging (DTI), and resting-state FMRI (rsFMRI)) to predict aphasia severity using Western Aphasia Battery-Revised Aphasia Quotient (WAB-R AQ) in ...
Differences in resting-state functional connectivity between depressed bipolar and major depressive disorder patients: A machine learning study.
European neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology
Jun 17, 2025
Nearly 60 % of individuals with bipolar disorder (BD) are initially classified as major depressive disorder (MDD) patients, resulting in inappropriate drug treatment. Identifying reliable biomarkers for the differential diagnosis between MDD and BD p...
Impact of Field-of-view Zooming and Segmentation Batches on Radiomics Features Reproducibility and Machine Learning Performance in Thyroid Scintigraphy.
Clinical nuclear medicine
Jun 17, 2025
BACKGROUND: Thyroid diseases are the second most common hormonal disorders, necessitating accurate diagnostics. Advances in artificial intelligence and radiomics have enhanced diagnostic precision by analyzing quantitative imaging features. However, ...
Development and interpretation of machine learning-based prognostic models for predicting high-risk prognostic pathological components in pulmonary nodules: integrating clinical features, serum tumor marker and imaging features.
Journal of cancer research and clinical oncology
Jun 17, 2025
BACKGROUND: With the improvement of imaging, the screening rate of Pulmonary nodules (PNs) has further increased, but their identification of High-Risk Prognostic Pathological Components (HRPPC) is still a major challenge. In this study, we aimed to ...
High-definition motion-resolved MRI using 3D radial kooshball acquisition and deep learning spatial-temporal 4D reconstruction.
Physics in medicine and biology
Jun 17, 2025
To develop motion-resolved volumetric MRI with 1.1 mm isotropic resolution and scan times <5 min using a combination of 3D radial kooshball acquisition and spatial-temporal deep learning 4D reconstruction for free-breathing high-definition (HD) lung ...
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