
Ain Shams Engineering Journal, Год журнала: 2024, Номер unknown, С. 103038 - 103038
Опубликована: Сен. 1, 2024
Язык: Английский
Ain Shams Engineering Journal, Год журнала: 2024, Номер unknown, С. 103038 - 103038
Опубликована: Сен. 1, 2024
Язык: Английский
Computer Science Review, Год журнала: 2024, Номер 53, С. 100662 - 100662
Опубликована: Авг. 1, 2024
Язык: Английский
Процитировано
13Multimedia Tools and Applications, Год журнала: 2024, Номер unknown
Опубликована: Авг. 20, 2024
Язык: Английский
Процитировано
12Multimedia Tools and Applications, Год журнала: 2024, Номер unknown
Опубликована: Июль 5, 2024
Язык: Английский
Процитировано
8Algorithms, Год журнала: 2025, Номер 18(2), С. 59 - 59
Опубликована: Янв. 22, 2025
This paper explores the overall picture regarding healthcare security systems through an extensive literature review. As sector has now become digitalized, of and, by extension, protection patient data is a key concern in modern era technological advances. Therefore, secure and integrated system essential. Thus, to evaluate relationship between quality, we conducted research identify studies reporting their association. The timeline our review based on published covering period from 2018 2024, with entries identified search relevant literature, focusing most recent developments due advances artificial intelligence algorithmic approaches. Thirty-two were included final survey. Our findings underscore critical role that significantly improve outcomes maintain integrity services. According approach, analyzed highlight growing importance advanced frameworks, especially those incorporating methodologies, safeguarding while enhancing care quality. this study, uses technology approaches, many researchers prove ransomware common threat hospital information systems, more are needed performance created against kind attack.
Язык: Английский
Процитировано
1Nanotechnology Reviews, Год журнала: 2024, Номер 13(1)
Опубликована: Янв. 1, 2024
Abstract The rapid expansion of nanotechnology has transformed numerous sectors, with nanoproducts now ubiquitous in everyday life, electronics, healthcare, and pharmaceuticals. Despite their widespread adoption, concerns persist regarding potential adverse effects, necessitating vigilant risk management. This systematic literature review advocates for leveraging artificial intelligence (AI) machine learning (ML) methodologies to enhance simulations refine safety assessments nanomaterials (NMs). Through a comprehensive examination the existing literature, this study seeks explain pivotal role AI boosting NMs sustainability efforts across six key research themes. It explores significance advancing sustainability, hazard identification, diverse applications field. In addition, it evaluates past strategies while proposing innovative avenues future exploration. By conducting analysis, aims illuminate current landscape, identify challenges, outline pathways integrating ML promote sustainable practices within nanotechnology. Furthermore, extending these technologies monitor real-world behaviour delivery. its thorough investigation, endeavours address obstacles pave way safe utilization nanotechnology, thereby minimizing associated risks.
Язык: Английский
Процитировано
6Expert Systems with Applications, Год журнала: 2024, Номер 255, С. 124554 - 124554
Опубликована: Июнь 25, 2024
Язык: Английский
Процитировано
4Engineering Research Express, Год журнала: 2024, Номер 6(2), С. 022202 - 022202
Опубликована: Июнь 1, 2024
Abstract Deep learning has shown tremendous potential for transforming healthcare by enabling more accurate diagnoses, improved treatment planning and better patient outcome predictions. In this comprehensive survey, we provide a detailed overview of the state-of-the-art deep techniques their applications across ecosystem. We first introduce fundamentals discuss its key advantages compared to traditional machine approaches. then present an in-depth review major in medical imaging, electronic health record analysis, genomics, robotics other domains. For each application, summarize advancements, outline technical details methods, challenges limitations highlight promising directions future work. examine cross-cutting deploying clinical settings, including interpretability, bias data scarcity. conclude proposing roadmap accelerate translation adoption high-impact learning. Overall, survey provides reference researchers practitioners working at intersection healthcare.
Язык: Английский
Процитировано
3Multimedia Tools and Applications, Год журнала: 2024, Номер unknown
Опубликована: Июнь 18, 2024
Язык: Английский
Процитировано
3Journal of Information Security and Applications, Год журнала: 2025, Номер 90, С. 104028 - 104028
Опубликована: Март 11, 2025
Язык: Английский
Процитировано
0Mathematics, Год журнала: 2025, Номер 13(6), С. 947 - 947
Опубликована: Март 13, 2025
Interior design, which integrates art and science, is vulnerable to infringements such as copying tampering. The unique often intricate nature of these designs makes them unauthorized replication misuse, posing significant challenges for designers seeking protect their intellectual property. To solve the above problems, we propose a deep learning-based zero-watermark copyright protection method. method aims embed undetectable information through image fusion technology without destroying interior design image. Specifically, fuses watermark learning generate highly robust This study also proposes verification network with U-Net verify validity extract efficiently. can accurately restore from protected images, thus effectively proving ownership work design. According on an experimental dataset, proposed in this against various image-oriented attacks. It avoids problem quality loss that traditional watermarking techniques may cause. Therefore, provide strong means field
Язык: Английский
Процитировано
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