Alruwaili (2020) proposed a hybrid strategy combining AI-based intelligent agents and BC to protect EHR databases. The authors Kumar et al. (2020) proposed a method for choosing miners using supervised learning and AI technology to maintain fairness in a healthcare-based system for mining data. Al-Safi et al. (2022) in crypto and blockchain articles their research, offered a decentralized method to preserve patient privacy in medical data using blockchain technology and utilizing an AI algorithm for classification and accuracy. Furthermore, Alzubi et al. (2022) provide a privacy-preserving EHR paradigm that identifies typical users and limits database access.
Benefits of Blockchains
Blockchain nodes ensure transparency, linking verified vaccination data through cryptographic hash functions (WHO 2020). In their paper Kumar et al. (2021a, b), the authors present a framework integrating DL and Blockchain for decentralized data learning in the context of Lung cancer prediction. Zerka et al. (2020) called this chained distributed machine learning C-DistriM, which is a revolutionary distributed learning approach that blends sequential distributed learning with a https://www.tokenexus.com/ Blockchain-based platform. Unlike a database of financial records stored by traditional institutions, the blockchain is completely transparent and aims to be distributed, shared across networks, and in many cases, fully public. By prioritizing transparency around transactions and how the information is stored, the blockchain can act as a single source of truth. This fusion of AI and blockchain technology transforms the healthcare workforce and skill sets (Sousa and Rocha 2019).
Data availability
IoT-based medication management systems can remind patients to take their medication and provide feedback to healthcare providers. IoT devices can facilitate communication and coordination between healthcare providers, caregivers, and patients, allowing for a more collaborative and integrated approach to rehabilitation137. IoT devices can gamify rehabilitation by providing rewards and incentives for meeting goals and milestones, which can improve patient engagement and compliance138.
Property Records
Blockchain’s Audibility features enable comprehensive auditing, tracing biased decisions back to their source. A study by Bose et al. (2024), explored addressing bias using blockchain smart contracts and the results show that blockchain contracts help maintain accurate data, which is crucial for reducing bias. Overall, blockchain enhances transparency, accountability, and audibility in AI decision-making.
Public Blockchain
Healthcare personnel must adapt to new technologies and workflows made by AI automation and blockchain data management solutions. This transition includes initiatives to upskill and reskill healthcare workers so that they can effectively employ new technologies to offer high-quality care. Furthermore, new roles such as AI specialists, blockchain developers, and data analysts arise, transforming the healthcare workforce and creating new opportunities. Blockchain technology serves as a powerful tool in fostering transparency and accountability in the utilization of AI algorithms (Zhou et al. 2024). The unalterable ledger of blockchain assures that every transaction and activity carried out by AI algorithms is forever recorded and cannot be changed (Wang et al. 2019a, b).
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- However, blockchain could also be used to process the ownership of real-life assets, like the deed to real estate and vehicles.
- This study offers valuable insights into the potential of blockchain technology to revolutionize the healthcare industry by addressing critical challenges and providing secure, interoperable, and compliant solutions.
- This layer ensures the confidentiality, integrity, and availability of IOMT data.
- IoMT devices can increase the risk of cybersecurity breaches and data privacy concerns, as these devices collect and transmit sensitive medical data.
- In each block, it has the attributes such as header, timestamp, nonce, data, and previous hash.
Higher Accuracy of Transactions
- If a hacker group wanted to manipulate any transaction on a blockchain, they would have to break into the device of every single network contributor around the world and change all records to show the same thing.
- CapsNet’s proficiency in capturing intricate data structures and providing interpretable features makes it a compelling approach for extracting valuable insights from unlabeled medical images (Sharma et al. 2023).
- Clustering is a method that groups comparable data points based on certain qualities or attributes without previous labeling (Xie et al. 2016).
- This challenge, in addition to the obstacles regarding scalability and standardization, will need to be addressed.
- (Generally, at least; we’ll deal with the caveats and exceptions later.) Instead of one company or person keeping track of everything, that responsibility is spread out to everyone on the network.
- Blockchain can help prevent overfitting across multiple classes by enhancing data accuracy through data augmentation techniques like flipping or rotating images (Tian et al. 2021).