This study focuses on English teachers' classroom language expression, emotional changes, and teacher-student interaction behaviors, and proposes an intelligent evaluation model based on multimodal representation learning-Bimodal Modality Representat...
This study aims to identify potential DYRK1A inhibitors from a curated database and utilize a QSAR model to predict the bioactivity of drug compounds in inhibiting the enzyme involved in tau protein oligomerization, a key process in AD pathology. 192...
Cardiovascular disease (CVD) remains the most common cause of death worldwide. Carotid plaque is an indicator of subclinical CVDs. Metabolic dysfunction-associated steatotic liver disease (MASLD) is a risk factor for atherosclerotic CVDs. We aimed to...
Sorafenib is the standard treatment for advanced hepatocellular carcinoma (HCC), yet resistance limits its efficacy. The Hedgehog (HH) signaling pathway contributes to drug resistance by maintaining HCC stem cell characteristics, but its role at the ...
Extant tourism studies on predicting tourist flow often adopt Backpropagation Neural Network (BP-NN) and Genetic Algorithm-Backpropagation Neural Network (GABP-NN). However, those models cannot well address the challenge of nonlinear complexity of to...
With the growing integration of social robots into pediatric environments, understanding and monitoring child-robot interaction has become increasingly important. Toward the advancement of biomechanical monitoring systems for pediatric applications, ...
The classification of human skin disorders, particularly benign and malignant skin cancer, is thoroughly examined in this study with a focus on protecting data privacy. Traditional visual diagnosis of skin disorders is often subjective and complicate...
Renal cell carcinomas (RCCs) are the seventh most widespread histological cancer. Around 40% of patients die in RCC due to the disease development. Thus, this tumour is the most lethal malignant urological tumour. The histopathologic classification o...
This study investigates the impact of generative artificial intelligence (GenAI) on engineering students' creativity, examining the mediating roles of critical thinking and AI self-efficacy in this relationship. We analyze the data collected using SP...
Detecting and segmenting brain tumors from 3D MRI images is a challenging and time-intensive task for clinicians. This research introduces an innovative hybrid architecture for deep learning, comprising a 3D fully convolutional neural network (3D-FCN...
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