As organizations transition toward data-driven strategies, the ability to anticipate unarticulated consumer needs has emerged as a critical frontier in strategic marketing. This study investigates how predictive analytics, when integrated with artifi...
English has emerged as the predominant global language, driving efforts to optimize its acquisition through interdisciplinary cognitive research. While behavioral studies suggest a link between English learning and mathematical cognition, the neural ...
BACKGROUND: The cross-modal conflict deficit is a key feature of schizophrenia. However, it remains largely unknown whether cross-modal conflict in schizophrenia diverges at distinct processing stages and its potential association with the auditory c...
International journal of psychophysiology : official journal of the International Organization of Psychophysiology
Jul 1, 2025
Poor sleep quality has been found to be associated with functional abnormalities in a few regions of the human brain. However, the brain is a dynamic network cooperation system, and it is necessary to study the relationship between sleep quality and ...
Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
Jul 1, 2025
BACKGROUND AND AIMS: Real-world studies on vedolizumab in inflammatory bowel disease (IBD) are often limited by small sample size and short follow-up. In this study, we investigated the 2-year effectiveness and safety of vedolizumab in patients with ...
This paper studies the influence of behavioral biases on Fintech adoption. Additionally, the role of financial literacy in adaptation of Fintech services is evaluated. Primary data from customers in the banking sector is gathered using a structured q...
BACKGROUND: The Aberrant Salience (AS) model conceptualizes psychosis onset as the altered attribution of salience to neutral stimuli. The Aberrant Salience Inventory (ASI), a psychometric tool, measures this phenomenon. This study utilized a multi-c...
OBJECTIVE: We aimed to develop a machine learning (ML) model to preoperatively predict surgical difficulty for pheochromocytomas and paragangliomas (PPGLs) using clinical and radiomic features.
BACKGROUND: People with psychosis have a higher suicide risk than the general population. Natural language processing (NLP) has been used to understand communication in psychosis and suicide risk prediction, but not to predict future suicidal behavio...
OBJECTIVE: Young adults face elevated risks from alcohol use yet encounter significant barriers to accessing evidence-based interventions. Large language models (LLMs) represent a promising advancement for delivering personalized behavioral intervent...
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