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Author

Riaz Rahman

Institution: Khulna University
ORCID: 0000-0001-6683-5906
Observed ORCID: 0000-0001-6683-5906
OpenAlex ID: A5063242458
A comparative study of machine learning algorithms for predicting domestic violence vulnerability in Liberian women
2023 · Riaz Rahman, Md. Nafiul Alam Khan, et al. · BMC Women s Health · 29
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Rural and urban differences in the prevalence and determinants of Type-2 diabetes in Bangladesh
2024 · Ashis Talukder, Sabiha Shirin Sara, et al. · PLoS ONE · 28
Prediction of suicidal ideation with associated risk factors among university students in the southern part of Bangladesh: Machine learning approach
2024 · Sabiha Shirin Sara, Md. Asikur Rahman, et al. · Journal of Affective Disorders · 27
Distribution of imposter syndrome among medical students of Bangladesh: a cross-sectional study
2021 · MD. SHAHJALAL, Md Nafiul Alam Khan, et al. · F1000Research · 10
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Determinants of developing cardiovascular disease risk with emphasis on type-2 diabetes and predictive modeling utilizing machine learning algorithms
2024 · Shatabdi Das, Riaz Rahman, et al. · Medicine · 9
Understanding and predicting pregnancy termination in Bangladesh: A comprehensive analysis using a hybrid machine learning approach
2024 · Riaz Rahman, Ashis Talukder, et al. · Medicine · 6
Android-Based Telemedicine System for Patient-Monitoring
2013 · M. A. Matin, Riaz Rahman · Advances in healthcare information systems and administration book series · 3
Identification of Significant Factors for Birth Mode in Bangladesh: Evidence From Cross-sectional Study
2022 · Fatheha Khatun, Riaz Rahman, et al. · Khulna University Studies · 2
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Gender-based differences of post COVID-19 suicidal ideation among the university students of southern part of Bangladesh: A cross-sectional study
2026 · Sabiha Shirin Sara, Chuton Deb Nath, et al. · Medicine
Mental Health Among University Students During Covid-19 Lockdown in Bangladesh: a Cross Sectional Study
2022 · Ashis Talukder, Riaz Rahman, et al. · Journal Of Healthcare In Developing Countries
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Works count: 10
Citation count: 112
H-index: 6
I10-index: 4
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