Exploring Malaria Endemicity Patterns and Tailored Interventions in Sudan Using Machine Learning

A Master of Science thesis in Computer Engineering by Fatimaelzahra Elnageeb Sulaiman Saeed entitled, “Exploring Malaria Endemicity Patterns and Tailored Interventions in Sudan Using Machine Learning”, submitted in June 2024. Thesis advisor is Dr. Assim Sagahyroon. Soft copy is available (Thesis, Co...

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Main Author: Saeed, Fatimaelzahra Elnageeb Sulaiman (author)
Format: doctoralThesis
Published: 2024
Subjects:
Online Access:https://hdl.handle.net/11073/25612
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author Saeed, Fatimaelzahra Elnageeb Sulaiman
author_facet Saeed, Fatimaelzahra Elnageeb Sulaiman
author_role author
dc.contributor.none.fl_str_mv Sagahyroon, Assim
dc.creator.none.fl_str_mv Saeed, Fatimaelzahra Elnageeb Sulaiman
dc.date.none.fl_str_mv 2024-09-23T10:13:08Z
2024-09-23T10:13:08Z
2024-06
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv 35.232-2024.23
https://hdl.handle.net/11073/25612
dc.language.none.fl_str_mv en_US
dc.subject.none.fl_str_mv Malaria
Targeted interventions
Malaria endemicity
Machine learning
Clustering analysis
Principal component analysis
dc.title.none.fl_str_mv Exploring Malaria Endemicity Patterns and Tailored Interventions in Sudan Using Machine Learning
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/doctoralThesis
description A Master of Science thesis in Computer Engineering by Fatimaelzahra Elnageeb Sulaiman Saeed entitled, “Exploring Malaria Endemicity Patterns and Tailored Interventions in Sudan Using Machine Learning”, submitted in June 2024. Thesis advisor is Dr. Assim Sagahyroon. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).
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identifier_str_mv 35.232-2024.23
language_invalid_str_mv en_US
network_acronym_str aus
network_name_str aus
oai_identifier_str oai:repository.aus.edu:11073/25612
publishDate 2024
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spelling Exploring Malaria Endemicity Patterns and Tailored Interventions in Sudan Using Machine LearningSaeed, Fatimaelzahra Elnageeb SulaimanMalariaTargeted interventionsMalaria endemicityMachine learningClustering analysisPrincipal component analysisA Master of Science thesis in Computer Engineering by Fatimaelzahra Elnageeb Sulaiman Saeed entitled, “Exploring Malaria Endemicity Patterns and Tailored Interventions in Sudan Using Machine Learning”, submitted in June 2024. Thesis advisor is Dr. Assim Sagahyroon. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).College of EngineeringDepartment of Computer Science and EngineeringMaster of Science in Computer Engineering (MSCoE)Sagahyroon, Assim2024-09-23T10:13:08Z2024-09-23T10:13:08Z2024-06info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdf35.232-2024.23https://hdl.handle.net/11073/25612en_USoai:repository.aus.edu:11073/256122025-06-26T12:22:56Z
spellingShingle Exploring Malaria Endemicity Patterns and Tailored Interventions in Sudan Using Machine Learning
Saeed, Fatimaelzahra Elnageeb Sulaiman
Malaria
Targeted interventions
Malaria endemicity
Machine learning
Clustering analysis
Principal component analysis
status_str publishedVersion
title Exploring Malaria Endemicity Patterns and Tailored Interventions in Sudan Using Machine Learning
title_full Exploring Malaria Endemicity Patterns and Tailored Interventions in Sudan Using Machine Learning
title_fullStr Exploring Malaria Endemicity Patterns and Tailored Interventions in Sudan Using Machine Learning
title_full_unstemmed Exploring Malaria Endemicity Patterns and Tailored Interventions in Sudan Using Machine Learning
title_short Exploring Malaria Endemicity Patterns and Tailored Interventions in Sudan Using Machine Learning
title_sort Exploring Malaria Endemicity Patterns and Tailored Interventions in Sudan Using Machine Learning
topic Malaria
Targeted interventions
Malaria endemicity
Machine learning
Clustering analysis
Principal component analysis
url https://hdl.handle.net/11073/25612