ArticleSensors (Basel, Switzerland)2023
RETRACTED: Blockchain-Powered Healthcare Systems: Enhancing Scalability and Security with Hybrid Deep Learning.
Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 21 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Blockchain-Based Dynamic and Revocable Consent for Secondary Health Data Use: Systematic Review.JMIR medical informatics · 2026Pooled it
- Blockchain in Health Information Systems: A Systematic Review.International journal of environmental research and public health · 2024Pooled it
- RETRACTED: Ali et al. Blockchain-Powered Healthcare Systems: Enhancing Scalability and Security with Hybrid Deep Learning.Sensors (Basel, Switzerland) · 2026Article
- Exploring Innovative Strategies to Enhance Electronic Health Record Interoperability in U.S. Healthcare Settings.Healthcare (Basel, Switzerland) · 2026Review
- Globalization in the Healthcare Industry: Drivers, Risks, and Adaptation.Healthcare (Basel, Switzerland) · 2026Review
- Blockchain in Cancer Care: Toward Evidence-Based and Inclusive Practice.Asian Pacific journal of cancer prevention : APJCP · 2026Article
- EnCTN: an enhanced AI-enabled deep learning framework for security enhancement in blockchain transactions.Scientific reports · 2025Article
- Characteristics of cohort data management systems (CDMS): a scoping review.BMC medical research methodology · 2025Article
- Digital Twin Cognition: AI-Biomarker Integration in Biomimetic Neuropsychology.Biomimetics (Basel, Switzerland) · 2025Review
- Enhancing confidentiality and access control in electronic health record systems using a hybrid hashing blockchain framework.Scientific reports · 2025Article
- Enhancing privacy in IoT-based healthcare using provable partitioned secure blockchain principle and encryption.Scientific reports · 2025Article
- Blockchain framework with IoT device using federated learning for sustainable healthcare systems.Scientific reports · 2025Article
- Writing the Future: Artificial Intelligence, Handwriting, and Early Biomarkers for Parkinson's Disease Diagnosis and Monitoring.Biomedicines · 2025Review
- Blockchain enabled deep learning model with modified coati optimization for sustainable healthcare disease detection and classification.Scientific reports · 2025Article
- Secure healthcare data sharing and attack detection framework using radial basis neural network.Scientific reports · 2025Article
- Enhancing Cancer Care through Blockchain Technology.Asian Pacific journal of cancer prevention : APJCP · 2025Review
- IBS-ECDHE: A blockchain-enhanced lightweight protocol for secure cloud-IoT in biomedical HCPS.Computational and structural biotechnology journal · 2025Article
- Privacy preservation in blockchain-based healthcare data sharing: A systematic review.Peer-to-peer networking and applications · 2025Review
- Effective Integration of Artificial Intelligence and Blockchain Technologies for Empowerment of Drug Discovery and Development.Current drug discovery technologies · 2025Review
- Review
Corrections and comments
- Retracted
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rapid advancements in technology have paved the way for innovative solutions in the healthcare domain, aiming to improve scalability and security while enhancing patient care. This abstract introduces a cutting-edge approach, leveraging blockchain technology and hybrid deep learning techniques to revolutionize healthcare systems. Blockchain technology provides a decentralized and transparent framework, enabling secure data storage, sharing, and access control. By integrating blockchain into healthcare systems, data integrity, privacy, and interoperability can be ensured while eliminating the reliance on centralized authorities. In conjunction with blockchain, hybrid deep learning techniques offer powerful capabilities for data analysis and decision making in healthcare. Combining the strengths of deep learning algorithms with traditional machine learning approaches, hybrid deep learning enables accurate and efficient processing of complex healthcare data, including medical records, images, and sensor data. This research proposes a permissions-based blockchain framework for scalable and secure healthcare systems, integrating hybrid deep learning models. The framework ensures that only authorized entities can access and modify sensitive health information, preserving patient privacy while facilitating seamless data sharing and collaboration among healthcare providers. Additionally, the hybrid deep learning models enable real-time analysis of large-scale healthcare data, facilitating timely diagnosis, treatment recommendations, and disease prediction. The integration of blockchain and hybrid deep learning presents numerous benefits, including enhanced scalability, improved security, interoperability, and informed decision making in healthcare systems. However, challenges such as computational complexity, regulatory compliance, and ethical considerations need to be addressed for successful implementation. By harnessing the potential of blockchain and hybrid deep learning, healthcare systems can overcome traditional limitations, promoting efficient and secure data management, personalized patient care, and advancements in medical research. The proposed framework lays the foundation for a future healthcare ecosystem that prioritizes scalability, security, and improved patient outcomes.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.