Analysis on dengue severity using machine learning approach

Analysis on dengue severity using machine learning approach

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.

Bibliografische gegevens
Hoofdauteurs:	Sayeed, Sanjana, Rashid, Iktisad, Sotej, Muktadir Rabbi
Andere auteurs:	Ajwad, Rasif
Formaat:	Thesis
Taal:	English
Gepubliceerd in:	Brac University 2021
Onderwerpen:	Dengue DSS DHF Supervised Unsupervised Hierarchical clustering Xg-boosting Clinical data Machine Learning
Online toegang:	http://hdl.handle.net/10361/15734

Gelijkaardige items

Seroprevalence and clinical characteristics investigation of Dengue virus infection in rural Bangladesh during 2019 Dengue outbreak
door: Rashed, Afsana
Gepubliceerd in: (2021)

Frequent dengue outbreaks in South Asian countries: analysis of associated risk factors and possible preventive measures
door: Islam, Mohibul
Gepubliceerd in: (2024)

An overview on the prevalence and diagnosis of dengue
door: Ashik-Uz- Zaman
Gepubliceerd in: (2018)

Detection of circulating dengue virus serotypes of 2021 dengue outbreak in Dhaka, Bangladesh
door: Rahmat, Raad
Gepubliceerd in: (2023)

Clinical evaluation of dengue and identification of risk factors for severe disease: protocol for a multicentre study in 8 countries
door: Jaenisch, Thomas, et al.
Gepubliceerd in: (2018)

Identifying the best metrics to find the best quality clusters of genes from gene expression data
door: Choudhury, Joydhriti, et al.
Gepubliceerd in: (2019)

Distinguish and management of the deadly co-infection caused by dengue virus and coronavirus in Bangladesh
door: Johora, Fatema-Tuz
Gepubliceerd in: (2024)

Global strategies for combating dengue Virus: a review on the control methods
door: Montasir, Fahim
Gepubliceerd in: (2024)

Demystifying machine learning models for IOT attack detection with explainable AI
door: Muna, Rabeya Khatun, et al.
Gepubliceerd in: (2021)

Drug utilization study in dengue infection in a tertiary care hospital in Bangladesh
door: Kundu, Sudipto
Gepubliceerd in: (2023)

A review on the surveillance methods of the aedes aegypti mosquito for the prevention of dengue
door: Hossain, Md.Murad
Gepubliceerd in: (2024)

A Study of gainful employment of learners receiving skills training in the informal sector using Machine Learning
door: Raizan, Syed Ahsan, et al.
Gepubliceerd in: (2021)

Prediction and detection in change of cognitive load for VIP’s by a machine learning approach
door: Rahman, Fahim, et al.
Gepubliceerd in: (2021)

Diseases to spread rapidly on insects: experts point at climate change
door: Palma, Porimol
Gepubliceerd in: (2016)

Developing a novel multi-epitope vaccine against Dengue virus targeting the Envelope protein using an Immunoinformatics approach
door: NASIFUZZAMAN, S M
Gepubliceerd in: (2021)

Role of statins as antagonists of 1DHF in cancer
door: Mustafa, Nashrah
Gepubliceerd in: (2018)

The economics of clusters

A new approach for processing X-ray data for detecting mini-halos in galaxy clusters
door: Jafar, Zareef, et al.
Gepubliceerd in: (2021)

3G and 4G paging success rate based mobile network anomaly detection using supervised and unsupervised learning
door: Ahasan, Md Rakibul
Gepubliceerd in: (2022)

Anomaly clustering based on correspondence analysis
door: Islam, Humayra
Gepubliceerd in: (2018)

Finding habitable exo planets using boosting algorithm
door: Rahman, Md. Mashfiq, et al.
Gepubliceerd in: (2020)

Speech emotion detection using supervised, unsupervised and feature selection algorithms
door: Rifat, Abu Nuraiya Mahfuza Yesmin, et al.
Gepubliceerd in: (2019)

Extractive text summarization using Fuzzy-c-means clustering
door: Gani, Shafiul
Gepubliceerd in: (2019)

Prediction of bipolar disorder from mental episodes using machine learning approach
door: Tasmeem, Sumaiya, et al.
Gepubliceerd in: (2023)

Education content provider based on particular weaknesses of students: a unsupervised machine learning appro
door: Rahman, Shabab Intishar, et al.
Gepubliceerd in: (2024)

A new tool to measure approaches to supervision from the perspective of community health workers: A prospective, longitudinal, validation study in seven countries
door: Vallières, Frédérique, et al.
Gepubliceerd in: (2022)

Qualitative classification of the breast cancer genome and clustering of the cancer gene network
door: Fatema, Kaniz, et al.
Gepubliceerd in: (2019)

Supervision in thought and action /
door: Lucio, William H.
Gepubliceerd in: (1979)

Why employees don't do what they're supposed to do and what to do about it /
door: Fournies, Ferdinand F.
Gepubliceerd in: (1988)

Early detection of chronic kidney disease using machine learning
door: Abrar, Tahmid, et al.
Gepubliceerd in: (2019)

Federated ensemble-learning for transport mode detection in vehicular edge network
door: Alam, MD. Mustakin, et al.
Gepubliceerd in: (2023)

Prediction on large scale data using extreme gradient boosting
door: Sawon, Md.Tariq Hasan, et al.
Gepubliceerd in: (2016)

Integration of data clustering to intelligent email classifier
door: Zisan, Shahriar Ahmed
Gepubliceerd in: (2019)

Detecting online recruitment fraud by using machine learning
door: Ghosh, Gitanjali, et al.
Gepubliceerd in: (2021)

Excellence in supervision : essential skills for the new supervisor /
door: Conlow, Rick
Gepubliceerd in: (2004)

তত্ত্বাবধান ও তত্ত্বাবধায়ক /
door: খান, মিসবাহউদ্দিন

Why employees don't do what they're supposed to do and what to do about it /
door: Fournies, Ferdinand F.
Gepubliceerd in: (1988)

Clustering web pages based on doc type structure in a distributed manner
door: Kader, Kazi Samiul, et al.
Gepubliceerd in: (2015)

Power, Powerlessness and Addiction
door: Jim Orford
Gepubliceerd in: (2013)

The Origins of Health and Disease
door: Michael E. Hyland
Gepubliceerd in: (2012)