Genetic algorithms with sharing for multimodal function optimization
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Using Genetic Algorithms for Concept Learning
Machine Learning - Special issue on genetic algorithms
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Database Mining: A Performance Perspective
IEEE Transactions on Knowledge and Data Engineering
Biometric Recognition: Security and Privacy Concerns
IEEE Security and Privacy
Communications of the ACM - Multimodal interfaces that flex, adapt, and persist
Classification of fingerprint images to real vs. spoof
International Journal of Biometrics
Clinical data privacy and customization via biometrics based on ECG signals
USAB'11 Proceedings of the 7th conference on Workgroup Human-Computer Interaction and Usability Engineering of the Austrian Computer Society: information Quality in e-Health
Journal of Medical Systems
Biometric verification of a subject through eye movements
Computers in Biology and Medicine
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The technology exists for the migration of healthcare data from its archaic paper-based system to an electronic one, and, once in digital form, to be transported anywhere in the world in a matter of seconds. The advent of universally accessible healthcare data has benefited all participants, but one of the outstanding problems that must be addressed is how the creation of a standardized nationwide electronic healthcare record system in the United Stateswould uniquely identify andmatch a composite of an individual's recorded healthcare information to an identified individual patients out of approximately 300 million people to a 1:1 match. To date, a few solutions to this problem have been proposed that are limited in their effectiveness.We propose the use of biometric technology within our fingerprint, iris, retina scan, and DNA (FIRD) framework, which is a multiphase system whose primary phase is a multilayer consisting of these four types of biometric identifiers: 1) fingerprint; 2) iris; 3) retina scan; and 4) DNA. In addition, it also consists of additional phases of integration, consolidation, and data discrepancy functions to solve the unique association of a patient to their medical data distinctively. This would allow a patient to have real-time access to all of their recorded healthcare information electronically whenever it is necessary, securely with minimal effort, greater effectiveness, and ease.