Epithelial ovarian cancer (EOC) is a lethal gynecological malignancy. Ongoing research aimed to identify novel biomarkers and develop combined algorithms to improve diagnosis and prognosis prediction for EOC. RNA-seq related to EOC were obtained from...
Deep learning models leveraging electronic health records (EHR) for opportunistic screening of type 2 diabetes (T2D) can improve current practices by identifying individuals who may need further glycemic testing. Accurate onset prediction and subtypi...
This study analyzes university students' attitudes towards artificial intelligence. Within the scope of the research, the data obtained from 1379 students through scale application were classified into three classes as "Insufficient", "Sufficient" an...
There is growing interest in using neuroimaging to understanding listening effort in individuals with hearing loss, with a particular focus on how innovative hearing aid features impact listening effort. This study used functional near infrared spect...
This study investigates how passengers perceive ride safety and develop trust in Robotaxi services in the absence of human drivers, with a focus on differences between daytime and nighttime scenarios. Drawing on the Elaboration Likelihood Model (ELM)...
This study investigates how personality traits, specifically those measured by the HEXACO Personality Inventory and the Dark Triad, predict university students' attitudes toward generative artificial intelligence (GAI) and their engagement in GAI-rel...
To develop and validate a machine learning (ML) model for predicting early recurrence (ER) within two years post-surgery in non-small cell lung cancer (NSCLC) patients. This multicenter cohort study included 3,171 NSCLC patients who underwent radical...
BACKGROUND: Subjective report of pain remains the gold standard for assessing symptoms in patients with chronic pain and their response to analgesics. This subjectivity underscores the importance of understanding patients' personal narratives, as the...
BACKGROUND: Preventive strategies integrated with digital health and artificial intelligence (AI) have significant potential to mitigate the global burden of atherosclerotic cardiovascular disease (ASCVD). AI-enabled clinical decision support (CDS) s...
BACKGROUND: Large language models (LLMs) have great potential to improve and make the work of clinicians more efficient. Previous studies have mainly focused on web-based services, such as ChatGPT, often with simulated cases. For the processing of pe...
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