We investigated event-related potentials (ERPs) in the context of autonomous vehicles (AVs)-specifically in ambiguous, morally challenging traffic situations. In our study, participants (n = 34) observed a putative artificial intelligence (AI) making...
This study proposes a novel approach to predict the efficacy of bevacizumab (BEV) in treating peritumoral edema in metastatic brain tumor patients by integrating advanced machine learning (ML) techniques with comprehensive imaging and clinical data. ...
With the extensive application of artificial intelligence technology in the tourism industry, robot-assisted tourism has become a vital strategy for enhancing tourist experiences and promoting sustainable tourism practices. This study aims to explore...
Heavy metal exposure is acknowledged as a risk factor for poor health. However, the effect of heavy metal exposure on the prevalence of gallstones is still unknown. Therefore, we investigated the relationship between heavy metal concentrations and th...
Postoperative nausea and vomiting (PONV) represent significant concerns for patients undergoing surgical procedures, as these symptoms greatly impact their postoperative experience. Among female patients undergoing laparoscopic surgery, the incidence...
Cancer imaging : the official publication of the International Cancer Imaging Society
May 8, 2025
OBJECTIVE: To evaluate the effectiveness of a simple positioning aid device in neck CT scans for the diagnosis of thyroid cancer, with a focus on its influence on image quality and diagnostic accuracy.
OBJECTIVE: This study validated the artificial intelligence (AI)-based algorithm LuxIA for screening more-than-mild diabetic retinopathy (mtmDR) from a single 45° colour fundus image of patients with diabetes mellitus (DM, type 1 or type 2) in Spain....
AIMS: Studies conducted during the COVID-19 pandemic found high occurrence of suicidal thoughts and behaviours (STBs) among healthcare workers (HCWs). The current study aimed to (1) develop a machine learning-based prediction model for future STBs us...
Cancer imaging : the official publication of the International Cancer Imaging Society
May 8, 2025
OBJECTIVE: Phyllodes tumors (PTs) are rare breast tumors with high recurrence rates, current methods relying on post-resection pathology often delay detection and require further surgery. We propose a deep-learning-based Phyllodes Tumors Hierarchical...
BACKGROUND AND OBJECTIVE: Accurate detection of schizophrenia poses a grand challenge as a complex and heterogeneous mental disorder. Current diagnostic criteria rely primarily on clinical symptoms, which may not fully capture individual differences ...