Despite decades of advancements in diagnostic MRI, 30%-50% of temporal lobe epilepsy (TLE) patients remain categorized as 'non-lesional' (i.e. MRI negative) based on visual assessment by human experts. MRI-negative patients face diagnostic uncertaint...
PURPOSE: This study explores the impact of AI-driven personalization, interactive features, and real-time feedback on user engagement and experience among marathon enthusiasts.
Mental health disorders like depression, anxiety, and stress (DAS) are rising globally. Understanding how diet and lifestyle influence these conditions is vital for targeted interventions. This study explores the potential of machine learning (ML) to...
Tension-type headache (TTH) is a primary headache with the highest prevalence. Previous studies have revealed the local brain abnormalities of TTH patients. However, little is known about its brain connectivity disruption. Based on rs-fMRI data from ...
Short sleep duration is associated with adverse physical and mental events. However, it is quite challenging to objectively quantify its impact on human cognitive performance. Thus, we aim to examine the effects of sleep deprivation on physiological ...
Word embeddings derived from large language corpora have been successfully used in cognitive science and artificial intelligence to represent linguistic meaning. However, there is continued debate as to how well they encode useful information about t...
The size of an individual's tongue relative to the oral cavity is associated with articulation speed [Feng, Lu, Zheng, Chi, and Honda, in Proceedings of the 10th Biennial Asia Pacific Conference on Speech, Language, and Hearing (2017), pp. 17-19)] an...
PURPOSE: To identify predictors of a true scaphoid fracture among patients with radial wrist pain following acute trauma, train 5 machine learning (ML) algorithms in predicting scaphoid fracture probability, and design a decision rule to initiate adv...
Deep learning frameworks utilizing convolutional neural networks (CNNs) have frequently been used for brain age prediction and have achieved outstanding performance. Nevertheless, deep learning remains a black box as it is hard to interpret which bra...
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