Cosmopolitan lifestyle and livelihood modifications have marked a toll on human health to the extent of myocardial disease onset at a relatively tender stage. One of the major issues that have been observed on the ris...
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Generative adversarial networks (GANs) have gained popularity for their ability to synthesize images from random inputs in deep learning models. One of the notable applications of this technology is the creation of re...
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Alzheimer’s disease(AD)is a neurological disorder that predominantly affects the *** the coming years,it is expected to spread rapidly,with limited progress in diagnostic *** machine learning(ML)and artificial intell...
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Alzheimer’s disease(AD)is a neurological disorder that predominantly affects the *** the coming years,it is expected to spread rapidly,with limited progress in diagnostic *** machine learning(ML)and artificial intelligence(AI)algorithms have been employed to detect AD using single-modality ***,recent developments in ML have enabled the application of these methods to multiple data sources and input modalities for AD *** this study,we developed a framework that utilizes multimodal data(tabular data,magnetic resonance imaging(MRI)images,and genetic information)to classify *** part of the pre-processing phase,we generated a knowledge graph from the tabular data and MRI *** employed graph neural networks for knowledge graph creation,and region-based convolutional neural network approach for image-to-knowledge graph ***,we integrated various explainable AI(XAI)techniques to interpret and elucidate the prediction outcomes derived from multimodal ***-wise relevance propagation was used to explain the layer-wise outcomes in the MRI *** also incorporated submodular pick local interpretable model-agnostic explanations to interpret the decision-making process based on the tabular data *** expression values play a crucial role in AD *** used a graphical gene tree to identify genes associated with the ***,a dashboard was designed to display XAI outcomes,enabling experts and medical professionals to easily comprehend the predic-tion results.
Binary classification of Thyroid has been observed in several manuscripts in literature. This study also classifies the disease using twelve machine learning algorithms. The results are compared with existing proposal...
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Academic information service is the most critical factor that must be considered in a university. Service quality is an important indicator affecting all academics’ satisfaction and loyalty. Improvement of informatio...
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A hashtag on X (Twitter) can attract a range of stakeholders with diverse perceptions on the hashtag. Under-standing and considering the differences between these stake-holders' perceptions on specific hashtags ca...
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The primary objective of this research endeavor was to comprehensively examine the influence of artificial intelligence (AI) applications, encompassing expert systems, neural networks, and genetic algorithms, on the q...
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ISBN:
(纸本)9781839539954
The primary objective of this research endeavor was to comprehensively examine the influence of artificial intelligence (AI) applications, encompassing expert systems, neural networks, and genetic algorithms, on the qualitative attributes of data within commercial banks listed on the Amman Stock Exchange. In order to fulfill the goals of this study, a dual-pronged methodology was adopted. The first approach was the descriptive-analytical method, which entailed the development of a questionnaire to gather primary data pertinent to the independent variables associated with AI applications. The second approach, the applied method, involved the assessment of the dependent variable, denoting the qualitative characteristics of data, utilizing the financial statements of commercial banks listed on the Amman Stock Exchange during the period spanning from 2015 to 2022. The analysis of data was conducted employing appropriate statistical techniques, and the formulated hypotheses underwent rigorous testing via multiple regression analysis. The findings derived from this study unveiled a noteworthy, statistically significant positive impact of varying magnitudes attributed to AI applications on the qualitative characteristics of data within the commercial banks listed on the Amman Stock Exchange. Specifically, the expert systems variable emerged as the foremost influencer, showcasing the highest strength of impact on the attainment of qualitative data characteristics. It was closely followed by the genetic algorithms variable, with the neural networks variable trailing in its impact. These results serve as a clarion call to the commercial banks in Jordan, urging them to bolster their utilization of AI domains and to encourage their effective application. This entails assigning a more prominent role to information technology (IT) experts, smart applications, and genetic algorithms. Such measures are aimed at ensuring the efficient and cost-effective utilization of AI domains, wi
Estimation of importance for considered features is an important issue for any knowledge exploration process and it can be executed by a variety of approaches. In the research reported in this study, the primary aim w...
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Liver cirrhosis is the fibrosis of liver caused by a long-term damage of the organ. This study classifies the disease in four classes based on a highly unbalanced dataset having 18 features and a data count of 6800 wi...
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Various pollutants like microplastics, oil spills, and chemical wastes contributing to water pollution are a global issue that has not yet found an end. Chemical dyes, which are widely used as food coloring and textil...
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