This study evaluates and compares the diagnostic and prognostic capabilities of ChatGPT-4o and DeepSeek-R1 in 56 HIV-negative talaromycosis cases. Clinical case fragments were de-identified and submitted to both models, with diagnostic accuracy and p...
This research explores the novel application of aromatic odors, specifically rosemary, in reducing mental workload, employing deep learning methods to analyze electroencephalogram (EEG) signals without feature extraction. Thirty volunteers participat...
Dental characteristics have considerable potential as indicators for estimating chronological age. This study developed a regression model for age estimation using dental characteristics observed in panoramic radiographs. A total of 2,391 radiographs...
Mental workload is an interdisciplinary construct that significantly influences human performance, particularly in tasks requiring sustained attention and cognitive processing. Effective mental workload assessment is critical for preventing cognitive...
Claustrophobia, a phobia with a specific unreasonable and excessive fear of enclosed spaces, can have a considerable impact on an individual's life. Electroencephalography (EEG) has been a tool with potential for studying neural processes in anxiety ...
Artificial Intelligence (AI) technologies are transforming educational settings by offering tools that enhance learning experiences. AI-powered applications, such as ChatGPT and Poe, provide real-time assistance, fostering learner autonomy and self-d...
As higher education becomes increasingly prevalent and accessible in China, a growing number of residents are afforded the option to pursue advanced studies. Can higher education genuinely enhance residents' subjective well-being? The response to thi...
AIM: Artificial intelligence anxiety refers to fear due to challenges caused by AI-related changes in one's own life. As the first study, our aim was to translate and validate the German version of the Artificial Intelligence Anxiety Scale (AIAS-G). ...
BACKGROUND: Young adults aged 25-49, at the peak of work and family responsibilities, face serious health and productivity challenges when affected by chronic kidney disease (CKD) due to hypertension.
Large language models (LLMs) increasingly mimic human cognition in various language-based tasks. However, their capacity for metacognition-particularly in predicting memory performance-remains unexplored. Here, we introduce a cross-agent prediction m...
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