Computers in Biology and Medicine, Год журнала: 2023, Номер 163, С. 107210 - 107210
Опубликована: Июль 3, 2023
Язык: Английский
Applied Sciences, Год журнала: 2024, Номер 14(2), С. 675 - 675
Опубликована: Янв. 12, 2024
Integrating Artificial Intelligence (AI) in healthcare represents a transformative shift with substantial potential for enhancing patient care. This paper critically examines this integration, confronting significant ethical, legal, and technological challenges, particularly privacy, decision-making autonomy, data integrity. A structured exploration of these issues focuses on Differential Privacy as critical method preserving confidentiality AI-driven systems. We analyze the balance between privacy preservation practical utility data, emphasizing effectiveness encryption, Privacy, mixed-model approaches. The navigates complex ethical legal frameworks essential AI integration healthcare. comprehensively examine rights nuances informed consent, along challenges harmonizing advanced technologies like blockchain General Data Protection Regulation (GDPR). issue algorithmic bias is also explored, underscoring urgent need effective detection mitigation strategies to build trust. evolving roles decentralized sharing, regulatory frameworks, agency are discussed depth. Advocating an interdisciplinary, multi-stakeholder approach responsive governance, aims align principles, prioritize patient-centered outcomes, steer towards responsible equitable enhancements
Язык: Английский
Процитировано
154
Information Fusion, Год журнала: 2023, Номер 102, С. 102060 - 102060
Опубликована: Сен. 29, 2023
The Internet of Medical Things (IoMT) has created a wide range opportunities for knowledge exchange in numerous industries. include patient empowerment, healthcare collaboration, medical education and training, remote monitoring telemedicine, customized treatment plans, data sharing innovation, continuous learning, supply chain management, public health initiatives, wearable devices, quality improvement initiatives. However, the adoption IoMT faces challenges regarding interoperability, privacy, security, regulatory, infrastructure costs. This paper aims to address implications fusion IoMT, as well associated security their potential solutions, which are lacking literature. Data collected from devices direct impact on accuracy predictions because its quality, quantity, relevance. With an 99.53% 99.99%, Epilepsy seizure detector-based Naive Bayes (ESDNB) algorithm is found be most effective detecting epileptic seizures networks. way stored must also undergo major revolution, all phases—collection, protection, storage—need improved. standardization architecture measures may improve detection threats compromises. Methods detect malware cross platforms avenue future research that can effectively tackle heterogeneity systems. Cryptography blockchain technology have shown promising ways increase IoMT-based system. findings this review will assist variety stakeholders ecosystem.
Язык: Английский
Процитировано
116
Knowledge-Based Systems, Год журнала: 2023, Номер 274, С. 110658 - 110658
Опубликована: Май 22, 2023
Recent developments in the Internet of Things (IoT) and various communication technologies have reshaped numerous application areas. Nowadays, IoT is assimilated into medical devices equipment, leading to progression Medical (IoMT). Therefore, IoMT-based healthcare applications are deployed used day-to-day scenario. Traditionally, machine learning (ML) models use centralized data compilation that impractical pragmatic frameworks due rising privacy security issues. Federated Learning (FL) has been observed as a developing distributed collective paradigm, most appropriate for modern framework, manages stakeholders (e.g., patients, hospitals, laboratories, etc.) carry out training without actual exchange sensitive data. Consequently, this work, authors present an exhaustive survey on FL-based IoMT smart frameworks. First, introduced devices, their types, applications, datasets, framework detail. Subsequently, concept FL, its domains, tools develop FL discussed. The significant contribution deploying secure systems presented by focusing patents, real-world projects, datasets. A comparison techniques with other schemes ecosystem also presented. Finally, discussed challenges faced potential future research recommendations deploy
Язык: Английский
Процитировано
91
Applied Soft Computing, Год журнала: 2023, Номер 136, С. 110119 - 110119
Опубликована: Фев. 16, 2023
Язык: Английский
Процитировано
69
AIMS Public Health, Год журнала: 2024, Номер 11(1), С. 58 - 109
Опубликована: Янв. 1, 2024
<abstract> <p>In recent years, machine learning (ML) and deep (DL) have been the leading approaches to solving various challenges, such as disease predictions, drug discovery, medical image analysis, etc., in intelligent healthcare applications. Further, given current progress fields of ML DL, there exists promising potential for both provide support realm healthcare. This study offered an exhaustive survey on DL system, concentrating vital state art features, integration benefits, applications, prospects future guidelines. To conduct research, we found most prominent journal conference databases using distinct keywords discover scholarly consequences. First, furnished along with cutting-edge ML-DL-based analysis smart a compendious manner. Next, integrated advancement services including ML-healthcare, DL-healthcare, ML-DL-healthcare. We then DL-based applications industry. Eventually, emphasized research disputes recommendations further studies based our observations.</p> </abstract>
Язык: Английский
Процитировано
48
Scientific Reports, Год журнала: 2024, Номер 14(1)
Опубликована: Март 4, 2024
Abstract During the COVID-19 pandemic, there has been a significant increase in use of internet resources for accessing medical care, resulting development and advancement Internet Medical Things (IoMT). This technology utilizes range equipment testing software to broadcast patient results over internet, hence enabling provision remote healthcare services. Nevertheless, preservation privacy security realm online communication continues provide pressing obstacle. Blockchain shown potential mitigate apprehensions across several sectors, such as industry. Recent advancements research have included intelligent agents monitoring systems by integrating blockchain technology. However, conventional network configuration agent introduces level complexity. In order address this disparity, we present proposed architectural framework that combines defined networking (SDN) with is specially tailored purpose facilitating within context 5G environment. The design contains patient-centric (PCA) inside SDN control plane managing user data on behalf patients. appropriate handling ensured PCA via essential instructions forwarding devices. suggested model assessed using hyperledger fabric docker-engine, its performance compared current models fifth generation (5G) networks. our surpasses methodologies, extensive study including factors throughput, dependability, overhead, packet error rate.
Язык: Английский
Процитировано
25
Опубликована: Фев. 9, 2024
Recent advancements in deep learning for healthcare and computer-aided laboratory services have sparked a renewed interest making medical data more accessible. Elevating the quality of delivering improved patient care necessitates knowledge base rooted data-driven insights. Deep models proven to excel this regard, as they are specifically designed embrace approach. These thrive on exposure larger datasets, which enables them continuously improve their performance. However, organizations strive aggregate clinical records onto central servers construct robust models, concerns surrounding privacy, ownership, legal restrictions emerged. Safeguarding sensitive while harnessing collective from multiple centers is challenging balancing act. One promising approach address these use privacy-preserving techniques that allow utilization without compromising security. Federated (FL) technique has emerged enable deployment large machine trained across necessity sharing information. In article, we present most recent findings derived systematic literature review focusing application federated settings. This offers insights into current state research practical implementations FL within domain. By leveraging learning, institutions can harness power upholding privacy security standards, ultimately leading effective solutions.
Язык: Английский
Процитировано
22
Health Science Reports, Год журнала: 2025, Номер 8(1)
Опубликована: Янв. 1, 2025
Artificial Intelligence (AI) beginning to integrate in healthcare, is ushering a transformative era, impacting diagnostics, altering personalized treatment, and significantly improving operational efficiency. The study aims describe AI including important technologies like robotics, machine learning (ML), deep (DL), natural language processing (NLP), investigate how these are used patient interaction, predictive analytics, remote monitoring. goal of this review present thorough analysis AI's effects on healthcare while providing stakeholders with road map for navigating changing environment. This analyzes the impact using data from Web Science (2014-2024), focusing keywords AI, ML, applications. It examines uses by synthesizing recent literature real-world case studies, such as Google Health IBM Watson Health, highlighting technologies, their useful applications, difficulties putting them into practice, problems security resource limitations. also discusses new developments they can affect society. findings demonstrate enhancing skills medical professionals, diagnosis, opening door more individualized treatment plans, reflected steady rise AI-related publications 158 articles (3.54%) 2014 731 (16.33%) 2024. Core applications monitoring analytics improve effectiveness involvement. However, there major obstacles mainstream implementation issues budget constraints. Healthcare may be transformed but its successful use requires ethical responsible use. To meet demands sector guarantee application evaluation highlights necessity ongoing research, instruction, multidisciplinary cooperation. In future, integrating responsibly will essential optimizing advantages reducing related dangers.
Язык: Английский
Процитировано
6
Nature Communications, Год журнала: 2025, Номер 16(1)
Опубликована: Апрель 2, 2025
Язык: Английский
Процитировано
4
International Journal of Communication Systems, Год журнала: 2023, Номер unknown
Опубликована: Фев. 6, 2023
Summary As an emerging technology, blockchain (BC) has been playing a promising role in today's software‐defined networking (SDN)‐enabled Internet of Things (IoT) applications. Because the salient feature network function virtualization (NFV) techniques, SDN can ensure IoT system runs efficiently and smoothly cloud‐driven ecosystem. When cloud‐enabled systems encounter immense security operational challenges caused mainly by third‐party dependency, large‐scale data communication, maintenance, BC offers effective robust transfer solutions without incorporating intermediaries over distributed network. With increased SDN‐BC convergence domain, underlying perspectives deserve proper attention methodically structurally. From motivation addressing such issues, this study provides necessary insights to combine those for successful plug‐and‐play. Therefore, includes purposefully investigating current state‐of‐the‐art extract research trends, future directions, domain. This comprehensive survey IoT, SDN, NFV, BC‐enabled technologies. More importantly, authors intelligently integrated four different technologies—IoT, BC, NFV based on characteristics, scopes, challenges, taxonomies, tables numerous areas. Initially, introduce SDN‐IoT ecosystem brief address features We took close look at SDN's overall taxonomy security, environment, challenges. also briefly describe integration with ecosystems. Moreover, we review prospect technology from perspectives, its extent, practical implementation, possible regarding smart Finally, highlights several directions these
Язык: Английский
Процитировано
40