TY - GEN
T1 - Securing Patient Personal Information Using Multi-Dimensional Anonymization-Based Intelligent Technology Using Edge Nodes
AU - Yadav, Abhinav
AU - Shukla, Marushika
AU - Yang, Tiansheng
AU - Rathore, Rajkumar Singh
AU - Tripathy, Hrudaya Kumar
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025/7/3
Y1 - 2025/7/3
N2 - Ensuring patient privacy is a primary concern when considering the integration of artificial intelligence in healthcare. Advanced models have the capability to utilize and safeguard diverse patient datasets, ensuring secure data exchange and concealing personal health information. They can adapt to enhance blended learning, blockchain, natural language processing, cybersecurity, biometric authentication, and other techniques. However, ethical considerations, such as defining limits and eliminating biases, pose significant challenges. To address these concerns, increasing transparency and minimizing prejudice are crucial steps for the ethical integration of AI. In summary, the adoption of artificial intelligence in healthcare presents a significant opportunity to enhance patient privacy by implementing safeguard measures against unauthorized access to private information.
AB - Ensuring patient privacy is a primary concern when considering the integration of artificial intelligence in healthcare. Advanced models have the capability to utilize and safeguard diverse patient datasets, ensuring secure data exchange and concealing personal health information. They can adapt to enhance blended learning, blockchain, natural language processing, cybersecurity, biometric authentication, and other techniques. However, ethical considerations, such as defining limits and eliminating biases, pose significant challenges. To address these concerns, increasing transparency and minimizing prejudice are crucial steps for the ethical integration of AI. In summary, the adoption of artificial intelligence in healthcare presents a significant opportunity to enhance patient privacy by implementing safeguard measures against unauthorized access to private information.
KW - Anonymization
KW - Blockchain
KW - Edge computing
KW - Healthcare
KW - Patient security
UR - https://www.scopus.com/pages/publications/105010579725
U2 - 10.1007/978-981-96-3250-3_28
DO - 10.1007/978-981-96-3250-3_28
M3 - Conference contribution
AN - SCOPUS:105010579725
SN - 9789819632497
T3 - Lecture Notes in Networks and Systems
SP - 349
EP - 358
BT - Proceedings of 4th International Conference on Computing and Communication Networks, ICCCN 2024
A2 - Kumar, Akshi
A2 - Swaroop, Abhishek
A2 - Shukla, Pancham
PB - Springer Science and Business Media Deutschland GmbH
T2 - 4th International Conference on Computing and Communication Networks, ICCCN 2024
Y2 - 17 October 2024 through 18 October 2024
ER -