OBJECTIVE: Empathy is a critical skill for effective counselling, yet novice counsellors often struggle to develop it. Traditional training methods may not sufficiently address the complexities of empathic development. This study aims to develop and ...
Computer methods and programs in biomedicine
Jun 4, 2025
BACKGROUND AND OBJECTIVE: Attention, cognitive workload/fatigue, and emotional states significantly influence learning outcomes, cognitive performance, and human-machine interactions. However, existing assessment methodologies fail to fully capture t...
International journal of legal medicine
Jun 4, 2025
Traditional age estimation methods based on macroscopic observation has been criticized for being excessively dependent on the observer's experience. The aim of this technical note is to propose a new atlas to assist the forensic practitioner in labe...
BACKGROUND: This study aims to build a machine learning (ML) model to predict the deterioration of neurological symptoms in Wilson's disease (WD) patients during short-term anti-copper therapy. The model combines brain T1WI MRI radiomics with clinica...
OBJECTIVE: This study developed and validated a deep learning model based on clinical and histopathological features for predicting the outcomes of diffuse large B-cell lymphoma (DLBCL).
Breast self-examination is a very cost-reducing approach that significantly decreases the cost burdens associated with medical equipment, fees of healthcare practitioners, transportation to health facilities, and other indirect costs. Furthermore, it...
This study focuses on the impact of learning experience on college students' deep learning of English and the chain-mediated effects of motivation and strategy. In the context of globalization, English is crucial for university students, but traditio...
This paper explores the relationship between Artificial Intelligence (AI) integration in the workplace, cultural orientation, and its impact on job autonomy and creative self-efficacy. Our study employs a mixed-method experimental design across 480 i...
This study investigates the similarities and differences in the analysis of human walking motion between the traditional inverse dynamics method and the forward dynamics method that employs an Artificial Neural Network (ANN)-based controller. Nine he...
Numerous studies have demonstrated that eyeblinks and other large artifacts can decrease the signal-to-noise ratio of EEG data, resulting in decreased statistical power for conventional univariate analyses. However, it is not clear whether eliminatin...
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