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              <text>An IoHT System Utilizing Smart Contracts for Machine Learning -Based Authentication</text>
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              <text>Artificial intelligence; blockchain technologies; E Healthcare; Internet of Healthcare Things (IoHT); Ma-chine learning; Random Forest; Support vector machines component</text>
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              <text>The Internet of Healthcare Things (IoHT) and blockchain technologies have made it feasible to share data in a secure and effective manner, but it is still challenging to ensure the data's veracity and privacy. This paper presents a blockchain authentication method that utilizes Machine Learning (ML) techniques that use smart contracts to ensure the security and privacy of IoHT data. The process utilizes smart contracts to manage access control and ensure data integrity, and deep learning algorithms to identify and validate the accuracy of user data. Furthermore, the approach improves the resilience and dependability of the authentication process and permits secure data ex-change between multiple IoHT systems. The proposed approach provides a potentially revolutionary solution to enhance the safety and confidentiality of IoHT data. It has the potential to fundamentally change how healthcare is provided in the future.  2023 IEEE.</text>
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              <text>Upreti K.; Vats P.; Borkhade G.; Raut R.D.; Hundekari S.; Parashar J.</text>
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              <text>2023 International Conference on Emerging Trends in Networks and Computer Communications, ETNCC 2023 - Proceedings, pp. 196-201.</text>
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              <text>Institute of Electrical and Electronics Engineers Inc.</text>
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              <text>&lt;a href="https://doi.org/10.1109/ETNCC59188.2023.10284960" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/ETNCC59188.2023.10284960&lt;/a&gt;
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              <text>Restricted Access</text>
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              <text>ISBN: 979-835031487-8</text>
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              <text>Online</text>
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              <text>Upreti K., CHRIST(Deemed to Be University), Dept. of Computer Science, Delhi NCR, Ghaziabad, India; Vats P., Scse Manipal University Jaipur, Dept. of Cse, Rajasthan, Jaipur, India; Borkhade G., Bharati Vidyapeeth College of Engineering, Dept. of Electronics &amp;amp; Telecommunication Engg, Maharashtra, Navi Mumbai, India; Raut R.D., Sant Gadge Baba Amravati University, Pgtd Applied Electronics, Maharashtra, Amravati, India; Hundekari S., Mit Adt University Loni Kalbhor, Pune, Pune, India; Parashar J., Adgitm, Dept. of Computer Science &amp;amp; Engg., New Delhi, India</text>
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