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Gulsum Alicioglu and Bo Sun
Deep learning (DL) models have achieved state-of-the-art performance in many domains. The interpretation of their working mechanisms and decision-making process is essential because of their complex structure and black-box nature, especially for sensitiv...
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Yongyao Jiang and Chaowei Yang
With recent advancements, large language models (LLMs) such as ChatGPT and Bard have shown the potential to disrupt many industries, from customer service to healthcare. Traditionally, humans interact with geospatial data through software (e.g., ArcGIS 1...
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Poornima Mahadevappa, Redhwan Al-amri, Gamal Alkawsi, Ammar Ahmed Alkahtani, Mohammed Fahad Alghenaim and Mohammed Alsamman
Edge data analytics refers to processing near data sources at the edge of the network to reduce delays in data transmission and, consequently, enable real-time interactions. However, data analytics at the edge introduces numerous security risks that can ...
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Rejath Jose, Faiz Syed, Anvin Thomas and Milan Toma
The advancement of machine learning in healthcare offers significant potential for enhancing disease prediction and management. This study harnesses the PyCaret library?a Python-based machine learning toolkit?to construct and refine predictive models for...
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Yogeswaranathan Kalyani, Liam Vorster, Rebecca Whetton and Rem Collier
In the last decade, digital twin (DT) technology has received considerable attention across various domains, such as manufacturing, smart healthcare, and smart cities. The digital twin represents a digital representation of a physical entity, object, sys...
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Shadi AlZu?bi, Mohammad Elbes, Ala Mughaid, Noor Bdair, Laith Abualigah, Agostino Forestiero and Raed Abu Zitar
Diabetes is a metabolic disorder in which the body is unable to properly regulate blood sugar levels. It can occur when the body does not produce enough insulin or when cells become resistant to insulin?s effects. There are two main types of diabetes, Ty...
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Nisrine Berros, Fatna El Mendili, Youness Filaly and Younes El Bouzekri El Idrissi
Medicine is constantly generating new imaging data, including data from basic research, clinical research, and epidemiology, from health administration and insurance organizations, public health services, and non-conventional data sources such as social ...
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Toh Yen Pang, Tsz-Kwan Lee and Manzur Murshed
This paper presents a new, fifth industrial revolution (Industry 5.0)-inspired paradigm for educating and training Australian healthcare professionals and students in the field of digital health. By leveraging Industry 5.0-enabling technologies, such as ...
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Gurtaj Singh, Vincenzo Violi and Marco Fisichella
Healthcare data are distributed and confidential, making it difficult to use centralized automatic diagnostic techniques. For example, different hospitals hold the electronic health records (EHRs) of different patient populations; however, transferring t...
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Fadwa Alrowais, Saud S. Alotaibi, Anwer Mustafa Hilal, Radwa Marzouk, Heba Mohsen, Azza Elneil Osman, Amani A. Alneil and Mohamed I. Eldesouki
Big Data analytics is a technique for researching huge and varied datasets and it is designed to uncover hidden patterns, trends, and correlations, and therefore, it can be applied for making superior decisions in healthcare. Drug?drug interactions (DDIs...
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