Clozapine is widely regarded as one of the most effective therapeutics for treatment-resistant schizophrenia. Despite its proven efficacy, the therapeutic use of clozapine is complicated by its narrow therapeutic index, which necessitates rapid and p...
Hand bone structure provides valuable features for sex estimation. This research introduces a novel approach using Artificial Intelligence (AI), specifically Convolutional Neural Networks (CNNs), to classify sex from hand X-ray images, focusing on th...
Accurate precipitation predictions are crucial for addressing climate change impacts on water resources, especially in arid regions like Oman. Therefore, this study evaluates three machine learning models-Random Forest (RF), Multilayer Perceptron Neu...
BACKGROUND: Predictive models like Residual Neural Networks (ResNets) can use Magnetic Resonance Imaging (MRI) data to identify cervix tumors likely to recur after radiotherapy (RT) with high accuracy. However, there persists a lack of insight into m...
BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is difficult to detect early and highly aggressive, often leading to poor patient prognosis. Existing serum biomarkers like CA19-9 are limited in early diagnosis, failing to meet clinical needs. Mac...
This study systematically analyzes the land use changes in Changsha City from 2000 to 2023. Three classification models-Random Forest (RF), Gradient Boosting Decision Tree (GBDT), and Artificial Neural Network (ANN) were employed to evaluate the accu...
Tools available for inferring enzyme function from general sequence, fold, or evolutionary information are generally successful. However, they can lead to misclassification if a deviation in local structural features influences the function. Here, we...
Deep Neural Networks (DNN) have achieved state-of-the-art performance in medical image classification and are increasingly being used for disease diagnosis. However, these models are quite complex and that necessitates the need to reduce the model co...
Extreme heat waves are causing widespread concern for comprehensive studies on their ecological and societal implications. With the ongoing rise in global temperatures, precise forecasting of heatwaves becomes increasingly crucial for proactive plann...
This study aims to explore a data-driven cultural background fusion method to improve the accuracy of environmental art image classification. A novel Dual Kernel Squeeze and Excitation Network (DKSE-Net) model is proposed for the complex cultural bac...
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