Internalizing problems (e.g., anxiety and depression) are associated with a wide range of adverse outcomes. While some predictors of internalizing problems are known (e.g., their frequent co-occurrence with neurodevelopmental (ND) conditions), the bi...
BACKGROUND: Identifying key areas of brain dysfunction in mental illness is critical for developing precision diagnosis and treatment. This study aimed to develop region-specific brain aging trajectory prediction models using multimodal magnetic reso...
BACKGROUND: Cerebellar atrophy is a known feature of ataxia-telangiectasia (A-T). However, basal ganglia dysfunction contributing to extrapyramidal movement disorders in A-T remains understudied.
Emotion regulation plays a crucial role in mental health, and difficulties in regulating emotions can contribute to psychological disorders. While reappraisal and suppression are well-studied strategies, the joint contributions of gray matter (GM) an...
Metacognition, the ability to reflect and regulate one's cognitive processes, has been shown to play a role in various aspects of life, particularly in academic settings. While important steps have been made in uncovering the neural basis of metacogn...
BACKGROUND: The onset of liver-related events (LREs) in fibrosis indicates a poor prognosis and worsens patients' quality of life, making the prediction and early detection of LREs crucial. The aim of this study was to develop a radiomics model using...
Knee Ailments, such as meniscus injuries, bother millions globally, with research showing that more than 14% of the population above 40 years lives with meniscus-related conditions. Conventional diagnosis techniques, like manual MRI interpretation, a...
Brain tumor classification (BTC) from Magnetic Resonance Imaging (MRI) is a critical diagnosis task, which is highly important for treatment planning. In this study, we propose a hybrid deep learning (DL) model that integrates VGG16, an attention mec...
OBJECTIVE: This study aims to develop a robust and clinically applicable framework for preoperative grading of meningiomas using T1-contrast-enhanced and T2-weighted MRI images. The approach integrates radiomic feature extraction, attention-guided de...
. AI-based neural decoding reconstructs visual perception by leveraging generative models to map brain activity measured through functional magnetic resonance imaging (fMRI) into the observed visual stimulus.. Traditionally, ridge linear models trans...
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