Determining fatal heart failure risks in patients diagnosed with chronic kidney disease: a machine learning approach
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022.
Main Authors: | Haque, Adiba, Kabir, Anika Nahian Binte, Islam, Maisha, Monjur, Mayesha |
---|---|
Outros Autores: | Rhaman, Md. Khalilur |
Formato: | Thesis |
Idioma: | English |
Publicado em: |
Brac University
2022
|
Assuntos: | |
Acesso em linha: | http://hdl.handle.net/10361/17028 |
Registos relacionados
-
In-hospital outcome of Diabetes patients with Chronic Kidney Disease
Por: Kabir, Sabrina
Publicado em: (2021) -
Prevalence of chronic kidney disease in South Asia: A systematic review
Por: Hasan, Mehedi, et al.
Publicado em: (2022) -
Global, regional, and national burden of chronic kidney disease, 1990–2017: A systematic analysis for the Global Burden of Disease Study 2017
Por: GBD Chronic Kidney Disease Collaboration
Publicado em: (2022) -
Characterization and analysis of the major risk factors of the Kidney Patients of Bangladesh: a retrospective study
Por: Rahman, Mahmud-Ur
Publicado em: (2018) -
Chronic kidney disease detection using ensemble classi ers and feature set reduction
Por: Shawan, Naveed Rahman, et al.
Publicado em: (2019)