Automated Symptom Tracking And Prediction Of Angioedema Disease Using Machine Learning-Reference-Cited by-同舟云学术

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Automated Symptom Tracking And Prediction Of Angioedema Disease Using Machine Learning

Published:2024-04-17 Issue: Volume:35 Page:1-6
ISSN:
Container-title:2024 International Conference on Communication, Computing and Internet of Things (IC3IoT)
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Author:

Arunkumar M¹,Palanisamy M²,Viknesh K³,Mugilarasan M¹,Abinesh B¹

Affiliation:

1. IFET College of Engineering,Dept. of Information Technology,Villupuram,Tamilnadu,India

2. Dhanalakshmi Srinivasan Engineering College,Dept. of Information Technology,Perambalur,Tamilnadu,India

3. IFET College of Engineering Villupuram, Tamilnadu,Dept. of Information Technology,Villupuram,Tamilnadu,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10550185/10550194/10550281.pdf?arnumber=10550281

Reference15 articles.

1. An update on the immunotoxic effects of arsenic exposure

2. Urticaria and Angioedema: Understanding Complex Pathomechanisms to Facilitate Patient Communication, Disease Management, and Future Treatment

3. Internet of Medical Things and Healthcare 4.0: Trends, Requirements, Challenges, and Research Directions

4. Acquired Angioedema Due to C1-Inhibitor Deficiency (AAE-C1-INH)—A Bicenter Retrospective Study on Diagnosis, Course, and Therapy

5. Quality of Life in Dermatology

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