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.
Egile Nagusiak: | Haque, Adiba, Kabir, Anika Nahian Binte, Islam, Maisha, Monjur, Mayesha |
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Beste egile batzuk: | Rhaman, Md. Khalilur |
Formatua: | Thesis |
Hizkuntza: | English |
Argitaratua: |
Brac University
2022
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Gaiak: | |
Sarrera elektronikoa: | http://hdl.handle.net/10361/17028 |
Antzeko izenburuak
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In-hospital outcome of Diabetes patients with Chronic Kidney Disease
nork: Kabir, Sabrina
Argitaratua: (2021) -
Prevalence of chronic kidney disease in South Asia: A systematic review
nork: Hasan, Mehedi, et al.
Argitaratua: (2022) -
Global, regional, and national burden of chronic kidney disease, 1990–2017: A systematic analysis for the Global Burden of Disease Study 2017
nork: GBD Chronic Kidney Disease Collaboration
Argitaratua: (2022) -
Characterization and analysis of the major risk factors of the Kidney Patients of Bangladesh: a retrospective study
nork: Rahman, Mahmud-Ur
Argitaratua: (2018) -
Chronic kidney disease detection using ensemble classi ers and feature set reduction
nork: Shawan, Naveed Rahman, et al.
Argitaratua: (2019)