Smart System for Dengue Fever Diagnosis: A Machine Learning Approach-Reference-Cited by-同舟云学术

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Smart System for Dengue Fever Diagnosis: A Machine Learning Approach

Published:2023-10-10 Issue: Volume: Page:
ISSN:
Container-title:2023 3rd International Conference on Emerging Smart Technologies and Applications (eSmarTA)
language:
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Author:

AL-Hagree Salah¹,Alalayah Khaled M.²,Al-Majmar Nashwan Ahmed¹,Mohsen Ayedh Abdulaziz³,Aqlan Amal⁴,Alhel-iani Mostafa⁵,Mohammed Merown¹,Albazel Mohammad⁵,Al-qasem Fahd⁵,Mohammed aljafari Motea⁵,Musleh Abdulbaset¹,Alnedam Ibrahim⁵

Affiliation:

1. Ibb University,Faculty of Sciences,Computer Science Department,Yemen

2. Computer Science, Ibb University, Yemen, Computer Science, Najran University,Saudi Arabia

3. Computer Science, Aljazeera University,Yemen

4. Computer Science, Ibb University, Yemen, King Khalid University, Community College,Department of Computer Sciences,Mohayel Aseer,Saudi Arabia

5. University of Science and Technology,Information Technology Department,Yemen

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10293182/10293222/10293518.pdf?arnumber=10293518

Reference28 articles.

1. Disease surveillance using online news: Dengue and zika in tropical countries

2. A personalized infectious disease risk prediction system

3. Classification rules using decision tree for dengue disease;rao;International Journal of Research in Computer and Communication Technology,2014

4. Early self-diagnosis of dengue symptoms using fuzzy and data mining approach

5. Predictive Models for the Medical Diagnosis of Dengue: A Case Study in Paraguay

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