Zobrazeno 1 - 10 of 15 pro vyhledávání: '"Md Menhazul Abedin"'
1
Akademický článek
Socioeconomic and demographic factors associated with low birth weight in Nepal: Data from 2016 Nepal demographic and health survey
Autor: Benojir Ahammed, Md Maniruzzaman, Farzana Ferdausi, Md Menhazul Abedin, Md Tanvir Hossain
Publikováno v: Social Health and Behavior, Vol 3, Iss 4, Pp 158-165 (2020)
Introduction: Low birth weight (LBW) is an essential component for child mortality, and it also has dangerous effects on the mother's health. This study attempted to estimate the prevalence of the LBW among Nepalese children as well as to identify it
Externí odkaz: https://doaj.org/article/74fae1b96f4c422d88a8b7963ad4d39b
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2
Akademický článek
Predicting risks of low birth weight in Bangladesh with machine learning.
Autor: S M Ashikul Islam Pollob, Md Menhazul Abedin, Md Touhidul Islam, Md Merajul Islam, Md Maniruzzaman
Publikováno v: PLoS ONE, Vol 17, Iss 5, p e0267190 (2022)
Background and objectiveLow birth weight is one of the primary causes of child mortality and several diseases of future life in developing countries, especially in Southern Asia. The main objective of this study is to determine the risk factors of lo
Externí odkaz: https://doaj.org/article/9992574dea8e4cbbb7d3f259284f3cf6
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3
Akademický článek
Investigate the risk factors of stunting, wasting, and underweight among under-five Bangladeshi children and its prediction based on machine learning approach.
Autor: S M Jubaidur Rahman, N A M Faisal Ahmed, Md Menhazul Abedin, Benojir Ahammed, Mohammad Ali, Md Jahanur Rahman, Md Maniruzzaman
Publikováno v: PLoS ONE, Vol 16, Iss 6, p e0253172 (2021)
AimsMalnutrition is a major health issue among Bangladeshi under-five (U5) children. Children are malnourished if the calories and proteins they take through their diet are not sufficient for their growth and maintenance. The goal of the research was
Externí odkaz: https://doaj.org/article/7721b46d18464663b51a15af57c4c0ec
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4
Akademický článek
Application of machine learning based algorithm for prediction of malnutrition among women in Bangladesh
Autor: Md. Merajul Islam, Md. Jahanur Rahman, Md Moidul Islam, Dulal Chandra Roy, N.A.M. Faisal Ahmed, Sadiq Hussain, Md Amanullah, Md. Menhazul Abedin, Md. Maniruzzaman
Publikováno v: International Journal of Cognitive Computing in Engineering, Vol 3, Iss , Pp 46-57 (2022)
Background and Objectives: Malnutrition among women is a major public health problem that has been linked to stunted growth, diabetes, and has adverse consequences for children, including low birth weight, less resistance to infections, and a higher
Externí odkaz: https://doaj.org/article/1665770edbc24995808c82b050a40d6a
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6
Determinants of different birth intervals of ever married women: Evidence from Bangladesh
Autor: Benojir Ahammed, Md. Menhazul Abedin, Md. Rasel Kabir, Md. Akhtarul Islam, Mohammad Ali
Publikováno v: Clinical Epidemiology and Global Health. 7:450-456
Introduction The analysis of factors affecting birth interval helps to reveal the mechanism and dynamics of fertility behavior which changes the population structure of a country. This study aims to examine the association among different socioeconom
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::582c397b1f0fe34b601c84c5db08b4b1
https://doi.org/10.1016/j.cegh.2019.01.011
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7
Statistical characterization and classification of colon microarray gene expression data using multiple machine learning paradigms
Autor: Jasjit S. Suri, Harman S. Suri, Benojir Ahammed, Mainak Biswas, Georgios Tsoulfas, Petros Bangeas, Ayman El-Baz, Md. Maniruzzaman, Md. Menhazul Abedin, Md. Jahanur Rahman
Publikováno v: Computer Methods and Programs in Biomedicine. 176:173-193
Objective A colon microarray data is a repository of thousands of gene expressions with different strengths for each cancer cell. It is necessary to detect which genes are responsible for cancer growth. This study presents an exhaustive comparative s
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e08816d9be83db6575cd671faa3b86af
https://doi.org/10.1016/j.cmpb.2019.04.008
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9
Comparative approaches for classification of diabetes mellitus data: Machine learning paradigm
Autor: Jasjit S. Suri, Harman S. Suri, Nishith Kumar, Md. Maniruzzaman, Ayman El-Baz, Md. Menhazul Abedin, Md. Shaykhul Islam
Publikováno v: Computer Methods and Programs in Biomedicine. 152:23-34
Introduce Gaussian process classification (GPC) technique for diabetes classification in machine learning framework.GPC uses three kernels types, namely: linear, polynomial and radial basis kernel.Comparison of GPC with existing classification techni
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ffa27eccf36eec1ffb6b9d86352d2d2f
https://doi.org/10.1016/j.cmpb.2017.09.004
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10
Classification and prediction of diabetes disease using machine learning paradigm
Autor: Md. Maniruzzaman, Md. Jahanur Rahman, Md. Menhazul Abedin, Benojir Ahammed
Publikováno v: Health Inf Sci Syst
BACKGROUND AND OBJECTIVES: Diabetes is a chronic disease characterized by high blood sugar. It may cause many complicated disease like stroke, kidney failure, heart attack, etc. About 422 million people were affected by diabetes disease in worldwide
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9eef8c4d58d64d264c3b655829458973
https://pubmed.ncbi.nlm.nih.gov/31949894
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