Disease Detection Based on Iris Recognition
Disease detection using iris recognition technology has emerged as a transformative paradigm in the realm of healthcare diagnostics. Leveraging the intricate patterns within the iris, this study explores the development and evaluation of a sophisticated machine learning model for disease identificat...
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Published in: | 2023 International Conference on Energy, Materials and Communication Engineering (ICEMCE) pp. 1 - 5 |
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Main Authors: | , , |
Format: | Conference Proceeding |
Language: | English |
Published: |
IEEE
14-12-2023
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Subjects: | |
Online Access: | Get full text |
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Summary: | Disease detection using iris recognition technology has emerged as a transformative paradigm in the realm of healthcare diagnostics. Leveraging the intricate patterns within the iris, this study explores the development and evaluation of a sophisticated machine learning model for disease identification. Through meticulous pre-processing and feature extraction, the iris patterns are translated into a comprehensive set of data points. Utilizing state-of-the-art machine learning algorithms, the model achieves a remarkable accuracy rate, revolutionizing the precision of disease diagnostics. Ethical considerations play a pivotal role in this research, with a strong emphasis on patient privacy and algorithmic fairness. Rigorous anonymization protocols and bias-mitigating strategies are integrated, ensuring that patient data is handled responsibly and diagnostic outcomes are equitable across diverse demographic groups. Looking forward, the potential applications of iris recognition in healthcare are vast. From real-time disease detection to secure access control within medical facilities, the technology's versatility promises transformative shifts in healthcare delivery. Moreover, the integration of iris recognition with telemedicine platforms opens doors for remote diagnostics, bridging healthcare disparities and ensuring accessibility to even the most remote populations. |
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DOI: | 10.1109/ICEMCE57940.2023.10433979 |