Integrating blockchain technology with artificial intelligence for the diagnosis of tibial plateau fractures DOI
Yi Xie,

Xiaoliang Chen,

Huiwen Yang

et al.

European Journal of Trauma and Emergency Surgery, Journal Year: 2025, Volume and Issue: 51(1)

Published: Feb. 21, 2025

Language: Английский

Deep learning: systematic review, models, challenges, and research directions DOI Creative Commons

Tala Talaei Khoei,

Hadjar Ould Slimane,

Naima Kaabouch

et al.

Neural Computing and Applications, Journal Year: 2023, Volume and Issue: 35(31), P. 23103 - 23124

Published: Sept. 7, 2023

Abstract The current development in deep learning is witnessing an exponential transition into automation applications. This can provide a promising framework for higher performance and lower complexity. ongoing undergoes several rapid changes, resulting the processing of data by studies, while it may lead to time-consuming costly models. Thus, address these challenges, studies have been conducted investigate techniques; however, they mostly focused on specific approaches, such as supervised learning. In addition, did not comprehensively other techniques, unsupervised reinforcement techniques. Moreover, majority neglect discuss some main methodologies learning, transfer federated online Therefore, motivated limitations existing this study summarizes techniques supervised, unsupervised, reinforcement, hybrid learning-based addition each category, brief description categories their models provided. Some critical topics namely, transfer, federated, models, are explored discussed detail. Finally, challenges future directions outlined wider outlooks researchers.

Language: Английский

Citations

122

A Survey of Blockchain and Artificial Intelligence for 6G Wireless Communications DOI
Yiping Zuo, Jiajia Guo, Ning Gao

et al.

IEEE Communications Surveys & Tutorials, Journal Year: 2023, Volume and Issue: 25(4), P. 2494 - 2528

Published: Jan. 1, 2023

The research on the sixth-generation (6G) wireless communications for development of future mobile communication networks has been officially launched around world. 6G face multifarious challenges, such as resource-constrained devices, difficult resource management, high complexity heterogeneous network architectures, explosive computing and storage requirements, privacy security threats. To address these deploying blockchain artificial intelligence (AI) in may realize new breakthroughs advancing performances terms security, privacy, efficiency, cost, more. In this paper, we provide a detailed survey existing works application AI to communications. More specifically, start with brief overview AI. Then, mainly review recent advances fusion AI, highlight inevitable trend both Furthermore, extensively explore integrating systems, involving secure services Internet Things (IoT) smart applications. Particularly, some most talked-about key based are introduced, spectrum computation allocation, content caching, privacy. Moreover, also focus important IoT applications supported by covering healthcare, transportation, grid, unmanned aerial vehicles (UAVs). thoroughly discuss operating frequencies, visions, requirements from perspective. We analyze open issues challenges joint deployment Lastly, lots meaningful works, paper aims comprehensive networks. hope can shed light newly emerging area serve roadmap studies.

Language: Английский

Citations

53

Blockchain security enhancement: an approach towards hybrid consensus algorithms and machine learning techniques DOI Creative Commons

K. Venkatesan,

Syarifah Bahiyah Rahayu

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Jan. 11, 2024

Abstract In this paper, we propose hybrid consensus algorithms that combine machine learning (ML) techniques to address the challenges and vulnerabilities in blockchain networks. Consensus Protocols make ensuring agreement among applicants distributed systems difficult. However, existing mechanisms are more vulnerable cyber-attacks. Previous studies extensively explore influence of cyber attacks highlight necessity for effective preventive measures. This research presents integration ML with proposed advantages over predicting cyber-attacks, anomaly detection, feature extraction. Our approaches leverage optimize protocols' security, trust, robustness. also explores various algorithms, such as Delegated Proof Stake Work (DPoSW), (PoSW), CASBFT (PoCASBFT), Byzantine (DBPoS) security enhancement intelligent decision making protocols. Here, demonstrate effectiveness methodology within decentralized networks using ProximaX platform. study shows framework is an energy-efficient mechanism maintains adapts dynamic conditions. It integrates privacy-enhancing features, robust mechanisms, detect prevent threats. Furthermore, practical implementation these ML-based models faces significant challenges, scalability, latency, throughput, resource requirements, potential adversarial attacks. These must be addressed ensure successful network real-world scenarios.

Language: Английский

Citations

48

On the Integration of Artificial Intelligence and Blockchain Technology: A Perspective About Security DOI Creative Commons
Alexandr Kuznetsov, Paolo Sernani, Luca Romeo

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 3881 - 3897

Published: Jan. 1, 2024

As reliance on disruptive applications based Artificial Intelligence (AI) and Blockchain grows, the need for secure trustworthy solutions becomes ever more critical. Whereas much research has been conducted AI Blockchain, there is a shortage of comprehensive studies examining their integration from security perspective. Hence, this survey addresses such gap provides insights policymakers, researchers, practitioners exploiting Blockchain's evolving integration. Specifically, paper analyzes potential benefits as well related concerns, identifying possible mitigation strategies, suggesting regulatory measures, describing impact it public trust.

Language: Английский

Citations

34

Privacy Preservation of Electronic Health Records in the Modern Era: A Systematic Survey DOI Open Access
Raza Nowrozy, Khandakar Ahmed, A. S. M. Kayes

et al.

ACM Computing Surveys, Journal Year: 2024, Volume and Issue: 56(8), P. 1 - 37

Published: March 19, 2024

Building a secure and privacy-preserving health data sharing framework is topic of great interest in the healthcare sector, but its success subject to ensuring privacy user data. We clarified definitions privacy, confidentiality security (PCS) because these three terms have been used interchangeably literature. found that researchers developers must address differences when developing electronic record (EHR) solutions. surveyed 130 studies on EHRs, techniques, tools were published between 2012 2022, aiming preserve EHRs. The observations findings summarized with help identified framed along survey questions addressed literature review. Our suggested usage access control, blockchain, cloud-based, cryptography techniques common for EHR sharing. commonly strategies preserving are implemented by various tools. Additionally, we collated comprehensive list similarities PCS. Finally, tabular form all proposed fusion better PCS

Language: Английский

Citations

32

The Convergence of Artificial Intelligence and Blockchain: The State of Play and the Road Ahead DOI Creative Commons
Dhanasak Bhumichai, Christos Smiliotopoulos, Ryan Benton

et al.

Information, Journal Year: 2024, Volume and Issue: 15(5), P. 268 - 268

Published: May 9, 2024

Artificial intelligence (AI) and blockchain technology have emerged as increasingly prevalent influential elements shaping global trends in Information Communications Technology (ICT). Namely, the synergistic combination of AI introduces beneficial, unique features with potential to enhance performance efficiency existing ICT systems. However, presently, confluence these two disruptive technologies remains a rather nascent stage, undergoing continuous exploration study. In this context, work at hand offers insight regarding most significant intersection. Sixteen outstanding, recent articles exploring been systematically selected thoroughly investigated. From them, fourteen key extracted, including data security privacy, encryption, sharing, decentralized intelligent systems, efficiency, automated decision collective making, scalability, system security, transparency, sustainability, device cooperation, mining hardware design. Moreover, drawing upon related literature stemming from major digital databases, we constructed timeline technological convergence comprising three eras: emerging, convergence, application. For era, categorized pertinent into primary groups: manipulation, applicability legacy issues. application elaborate on impact fusion perspective five distinct focus areas, Internet Things applications cybersecurity, finance, energy, smart cities. This multifaceted, but succinct analysis is instrumental delineating pinpointing characteristics inherent their integration. The paper culminates by highlighting prevailing challenges unresolved questions AI-based thereby charting avenues for future scholarly inquiry.

Language: Английский

Citations

24

Evaluation and prioritization of artificial intelligence integrated block chain factors in healthcare supply chain: A hybrid Decision Making Approach DOI Creative Commons

Neda Seifi,

Erfan Ghoodjani,

Seyed Shabahang Majd

et al.

Computer and decision making., Journal Year: 2025, Volume and Issue: 2, P. 374 - 405

Published: Jan. 5, 2025

The integration of artificial intelligence and blockchain in healthcare promises a significant transformation data management, service quality improvement, increased patient security. Blockchain, by offering decentralized transparent platform, enhances the reliability security information. Meanwhile, intelligence, with its ability to analyse process data, helps identify patterns predict treatment outcomes. aim this study is Evaluation prioritization integrated factors supply chain using F-AHP F-DEMATEL. Following review previous studies, four criteria 23 sub-criteria were identified. In first step, these ranked method. second relationships among determined through F-DEMATEL, identifying causal effect criteria. results show that identified from "integration processes (C32)", "Provide fair (C31)", "health monitoring (C12)", "security medical (C34)", "clinical decision support (C21)" fifth, respectively. F-DEMATEL indicate are divided into categories, "stakeholder participation (C42)" "technology acceptance (C44)" being most important sub-criteria, while "monitoring (C15)" "patient-centered strategies (C22)" as sub-criteria. These findings suggest use AI-blockchain can lead improvements managing systems.

Language: Английский

Citations

10

Addressing challenges of digital transformation with modified blockchain DOI
Gajendra Liyanaarachchi, Giampaolo Viglia, Fidan Kurtaliqi

et al.

Technological Forecasting and Social Change, Journal Year: 2024, Volume and Issue: 201, P. 123254 - 123254

Published: Feb. 2, 2024

Language: Английский

Citations

12

Machine Learning and Blockchain: A Bibliometric Study on Security and Privacy DOI Creative Commons
Alejandro Valencia-Arías, Juan David González-Ruíz,

Lilian Verde Flores

et al.

Information, Journal Year: 2024, Volume and Issue: 15(1), P. 65 - 65

Published: Jan. 22, 2024

Machine learning and blockchain technology are fast-developing fields with implications for multiple sectors. Both have attracted a lot of interest show promise in security, IoT, 5G/6G networks, artificial intelligence, more. However, challenges remain the scientific literature, so aim is to investigate research trends around use machine blockchain. A bibliometric analysis proposed based on PRISMA-2020 parameters Scopus Web Science databases. An objective most productive highly cited authors, journals, countries conducted. Additionally, thorough keyword validity importance performed, along review significant topics by year publication. Co-occurrence networks generated identify crucial clusters field. Finally, agenda highlight future great potential. This study reveals growing Topics evolving towards IoT smart contracts. Emerging keywords include cloud computing, intrusion detection, distributed learning. The United States, Australia, India leading research. proposes an explore new applications foster collaboration between researchers this interdisciplinary

Language: Английский

Citations

9

Deep learning on medical image analysis DOI Creative Commons
Jiaji Wang, Shuihua Wang‎, Yudong Zhang

et al.

CAAI Transactions on Intelligence Technology, Journal Year: 2024, Volume and Issue: unknown

Published: June 24, 2024

Abstract Medical image analysis plays an irreplaceable role in diagnosing, treating, and monitoring various diseases. Convolutional neural networks (CNNs) have become popular as they can extract intricate features patterns from extensive datasets. The paper covers the structure of CNN its advances explores different types transfer learning strategies well classic pre‐trained models. also discusses how has been applied to areas within medical analysis. This comprehensive overview aims assist researchers, clinicians, policymakers by providing detailed insights, helping them make informed decisions about future research policy initiatives improve patient outcomes.

Language: Английский

Citations

9