Maniruzzaman M - Search Results

1

Comparative approaches for classification of diabetes mellitus data: Machine learning paradigm.

Maniruzzaman M, Kumar N, Menhazul Abedin M, Shaykhul Islam M, Suri HS, El-Baz AS, Suri JS. Maniruzzaman M, et al. Comput Methods Programs Biomed. 2017 Dec;152:23-34. doi: 10.1016/j.cmpb.2017.09.004. Epub 2017 Sep 8. Comput Methods Programs Biomed. 2017. PMID: 29054258

2

Socioeconomic inequality in the prevalence of low birth weight and its associated determinants in Bangladesh.

Alam MJ, Islam MM, Maniruzzaman M, Ahmed NAMF, Tawabunnahar M, Rahman MJ, Roy DC, Mydam J. Alam MJ, et al. Among authors: maniruzzaman m. PLoS One. 2022 Oct 27;17(10):e0276718. doi: 10.1371/journal.pone.0276718. eCollection 2022. PLoS One. 2022. PMID: 36301890 Free PMC article.

3

Accurate Diabetes Risk Stratification Using Machine Learning: Role of Missing Value and Outliers.

Maniruzzaman M, Rahman MJ, Al-MehediHasan M, Suri HS, Abedin MM, El-Baz A, Suri JS. Maniruzzaman M, et al. J Med Syst. 2018 Apr 10;42(5):92. doi: 10.1007/s10916-018-0940-7. J Med Syst. 2018. PMID: 29637403 Free PMC article.

4

Risk factors of neonatal mortality and child mortality in Bangladesh.

Maniruzzaman M, Suri HS, Kumar N, Abedin MM, Rahman MJ, El-Baz A, Bhoot M, Teji JS, Suri JS. Maniruzzaman M, et al. J Glob Health. 2018 Jun;8(1):010417. doi: 10.7189/jogh.08.010421. J Glob Health. 2018. PMID: 29740501 Free PMC article.

5

Morphologic TPA (mTPA) and composite risk score for moderate carotid atherosclerotic plaque is strongly associated with HbA1c in diabetes cohort.

Cuadrado-Godia E, Maniruzzaman M, Araki T, Puvvula A, Jahanur Rahman M, Saba L, Suri HS, Gupta A, Banchhor SK, Teji JS, Omerzu T, Khanna NN, Laird JR, Nicolaides A, Mavrogeni S, Kitas GD, Suri JS; Fellow AIMBE. Cuadrado-Godia E, et al. Among authors: maniruzzaman m. Comput Biol Med. 2018 Oct 1;101:128-145. doi: 10.1016/j.compbiomed.2018.08.008. Epub 2018 Aug 8. Comput Biol Med. 2018. PMID: 30138774

6

Ranking of stroke and cardiovascular risk factors for an optimal risk calculator design: Logistic regression approach.

Cuadrado-Godia E, Jamthikar AD, Gupta D, Khanna NN, Araki T, Maniruzzaman M, Saba L, Nicolaides A, Sharma A, Omerzu T, Suri HS, Gupta A, Mavrogeni S, Turk M, Laird JR, Protogerou A, Sfikakis P, Kitas GD, Viswanathan V, Suri JS. Cuadrado-Godia E, et al. Among authors: maniruzzaman m. Comput Biol Med. 2019 May;108:182-195. doi: 10.1016/j.compbiomed.2019.03.020. Epub 2019 Mar 25. Comput Biol Med. 2019. PMID: 31005010

7

Statistical characterization and classification of colon microarray gene expression data using multiple machine learning paradigms.

Maniruzzaman M, Jahanur Rahman M, Ahammed B, Abedin MM, Suri HS, Biswas M, El-Baz A, Bangeas P, Tsoulfas G, Suri JS. Maniruzzaman M, et al. Comput Methods Programs Biomed. 2019 Jul;176:173-193. doi: 10.1016/j.cmpb.2019.04.008. Epub 2019 Apr 10. Comput Methods Programs Biomed. 2019. PMID: 31200905

8

Classification and prediction of diabetes disease using machine learning paradigm.

Maniruzzaman M, Rahman MJ, Ahammed B, Abedin MM. Maniruzzaman M, et al. Health Inf Sci Syst. 2020 Jan 3;8(1):7. doi: 10.1007/s13755-019-0095-z. eCollection 2020 Dec. Health Inf Sci Syst. 2020. PMID: 31949894 Free PMC article.

9

Automated detection and classification of diabetes disease based on Bangladesh demographic and health survey data, 2011 using machine learning approach.

Islam MM, Rahman MJ, Chandra Roy D, Maniruzzaman M. Islam MM, et al. Among authors: maniruzzaman m. Diabetes Metab Syndr. 2020 May-Jun;14(3):217-219. doi: 10.1016/j.dsx.2020.03.004. Epub 2020 Mar 10. Diabetes Metab Syndr. 2020. PMID: 32193086

10

Risk prediction of diabetic nephropathy using machine learning techniques: A pilot study with secondary data.

Maniruzzaman M, Islam MM, Rahman MJ, Hasan MAM, Shin J. Maniruzzaman M, et al. Diabetes Metab Syndr. 2021 Sep-Oct;15(5):102263. doi: 10.1016/j.dsx.2021.102263. Epub 2021 Aug 28. Diabetes Metab Syndr. 2021. PMID: 34482122

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