BACKGROUND: Large language models (LLMs) offer significant potential to streamline research workflows and enhance productivity. However, limited data exist on the extent of their adoption within the mental health research community.
BACKGROUND: Accumulating evidence suggests that migraine patients present abnormal brain responses to salient sensory and emotional stimuli. However, it is still unclear whether this is a generalized or domain-specific phenomenon. Employing a well-va...
Journal of cancer research and clinical oncology
Jun 12, 2025
PURPOSE: This study aimed to evaluate radiomic models' ability to predict hypoxia-related biomarker expression in clear cell renal cell carcinoma (ccRCC).
Cephalalgia : an international journal of headache
Jun 12, 2025
BackgroundUnderstanding characteristics and reasons associated with using calcitonin gene-related peptide monoclonal antibodies (CGRP mAb) for migraine prevention may help clinicians individualize treatment plans and achieve better patient outcomes.M...
BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental condition with increasing prevalence worldwide. Air pollution may be a major contributor to the rise in ASD cases. This study investigated how the risk of ASD associated with prenatal...
This study introduces an advanced computational model for simulating surface electromyography (sEMG) signals during muscle contractions. The model integrates five elements that simulate the chain of processes from motor intention to voltage variation...
Approaches studying the dynamics of resting-state functional magnetic resonance imaging (rs-fMRI) activity often focus on time-resolved functional connectivity (tr-FC). While many tr-FC approaches have been proposed, most are linear approaches, e.g. ...
OBJECTIVE: This study aimed to develop an innovative early prediction model for acute kidney injury (AKI) following cardiac surgery in intensive care unit (ICU) settings, leveraging preoperative and postoperative clinical variables, and to identify k...
OBJECTIVES: To develop and validate a deep learning model based on three-dimensional features (DL_3D) for distinguishing lung adenocarcinoma (LUAD) from tuberculoma (TBM).
Cognitive processes preceding suicidal attempts (SA) remain poorly understood, particularly in distinguishing those who act on suicidal thoughts from those who do not. This study compared proximal contemplation and planning processes during suicidal ...
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