Blockchain technology to secure medical data sharing in machine learning applications ensure privacy and integrity
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M. Parthiban
Abstract
The idea of blockchainblockchain provides unprecedented answers for brand new challenges with EHR structures with great disruption in the healthcare field. In this chapter an overview of the effects and possibilities of the uncontrolled growth of the blockchain technologytechnology in the acquisition, preservation, and dissemination of data in healthcare is described. After much research on the blockchain-based EHREHR systems, a number of interconnected applications that comprise data sharing, security, and patient-oriented EHRs has been developed. It was to mention that in the case of data sharing, and especially concerning the topic of privacy and securitysecurity and where there is no ability to change data, stakeholders of healthcarehealthcare facilities find blockchain an extremely effective tool for data sharing. Consensus process, smart contract, and encryption thus improve the security measures even further while giving the patients the most absolute control over their healthhealth information. It shifted to actual application scenarios and asked what blockchain means for blockchained healthcare systems and matter interaction and brought together numerous parties. The fluctuations witnessed within the landscapelandscape reveal what the future of blockchain adoption in the healthcare sector can entail in the right direction, how far the healthcare industry has come in blockchain, and how far it has to go in developing more practical and coordinated plans and visions to understand where blockchain can actually revolutionize the flow of the health initiative, favorable outcomes, and substantial end-user value proposition.
Abstract
The idea of blockchainblockchain provides unprecedented answers for brand new challenges with EHR structures with great disruption in the healthcare field. In this chapter an overview of the effects and possibilities of the uncontrolled growth of the blockchain technologytechnology in the acquisition, preservation, and dissemination of data in healthcare is described. After much research on the blockchain-based EHREHR systems, a number of interconnected applications that comprise data sharing, security, and patient-oriented EHRs has been developed. It was to mention that in the case of data sharing, and especially concerning the topic of privacy and securitysecurity and where there is no ability to change data, stakeholders of healthcarehealthcare facilities find blockchain an extremely effective tool for data sharing. Consensus process, smart contract, and encryption thus improve the security measures even further while giving the patients the most absolute control over their healthhealth information. It shifted to actual application scenarios and asked what blockchain means for blockchained healthcare systems and matter interaction and brought together numerous parties. The fluctuations witnessed within the landscapelandscape reveal what the future of blockchain adoption in the healthcare sector can entail in the right direction, how far the healthcare industry has come in blockchain, and how far it has to go in developing more practical and coordinated plans and visions to understand where blockchain can actually revolutionize the flow of the health initiative, favorable outcomes, and substantial end-user value proposition.
Kapitel in diesem Buch
- Frontmatter I
- Contents V
- List of contributors VII
- Blockchain technology to secure medical data sharing in machine learning applications ensure privacy and integrity 1
- AI-powered sensors and devices for sustained health tracking 39
- Development of AI-driven biomedical sensors and devices optimization for continuous health monitoring 89
- Design and development of AI-driven biomedical sensors and devices and their optimization for continuous health monitoring 131
- Machine learning-driven personalized medicine: customized drug delivery systems and patient-specific material applications 193
- Personalized medicine using customized drug delivery systems and patient-specific material solutions, enabled by machine learning algorithms 239
- AI-driven drug design exploring molecular docking and lead optimization using machine learning algorithms 297
- Machine learning models for predicting drug toxicity and side effects 335
- Machine learning innovations in biomedical materials from drug discovery to personalized medicine 395
- High-throughput screening for novel medical materials: machine learning-enabled approaches 445
- Automated materials characterization using machine learning for screening biocompatible materials 489
- Machine learning algorithms for enhanced medical image analysis and diagnostics 541
- Transforming healthcare with machine learning 585
- Revolutionizing healthcare 635
- Index 687
- De Gruyter Series in Advanced Mechanical Engineering
Kapitel in diesem Buch
- Frontmatter I
- Contents V
- List of contributors VII
- Blockchain technology to secure medical data sharing in machine learning applications ensure privacy and integrity 1
- AI-powered sensors and devices for sustained health tracking 39
- Development of AI-driven biomedical sensors and devices optimization for continuous health monitoring 89
- Design and development of AI-driven biomedical sensors and devices and their optimization for continuous health monitoring 131
- Machine learning-driven personalized medicine: customized drug delivery systems and patient-specific material applications 193
- Personalized medicine using customized drug delivery systems and patient-specific material solutions, enabled by machine learning algorithms 239
- AI-driven drug design exploring molecular docking and lead optimization using machine learning algorithms 297
- Machine learning models for predicting drug toxicity and side effects 335
- Machine learning innovations in biomedical materials from drug discovery to personalized medicine 395
- High-throughput screening for novel medical materials: machine learning-enabled approaches 445
- Automated materials characterization using machine learning for screening biocompatible materials 489
- Machine learning algorithms for enhanced medical image analysis and diagnostics 541
- Transforming healthcare with machine learning 585
- Revolutionizing healthcare 635
- Index 687
- De Gruyter Series in Advanced Mechanical Engineering
