Author

Melaku Alelign Mengstie

Observed names: Melaku Alelign, Melaku Alelign Mengistie, Melaku Mengstie

Observed institution: University of Gondar

ORCID: 0009-0009-2835-7339

Observed ORCID: 0009-0009-2835-7339

OpenAlex ID: A5115000460

Applying transfer learning in CNN model architectures for detecting tomato leaf disease with explainable artificial intelligence

2025 · Alexander Takele Mengesha, Melaku Alelign Mengistie · Smart Agricultural Technology · 19

The lifetime prevalence and associated factors of suicidal ideation and suicide attempts among high school adolescents in Ethiopia: a systematic review and meta-analysis

2025 · Berhan Tekeba, Tadesse Tarik Tamir, et al. · Child and Adolescent Psychiatry and Mental Health · 9

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Investigate Risk Factors and Predict Neonatal and Infant Mortality Based on Maternal Determinants using Homogenous Ensemble Methods

2021 · Tizita Dereje, Tesfamariam M Abuhay, et al. · International Conference on Information and Communication Technology for Development for Africa (ICT4DA) · 6

Identifying Risk Factors and Predicting Food Security Status using Supervised Machine Learning Techniques

2021 · Melaku Alelign, Tesfamariam M Abuhay, et al. · International Conference on Information and Communication Technology for Development for Africa (ICT4DA) · 5

Predicting neonatal mortality using ensemble machine learning algorithms in the case of Ethiopian Rural Areas

2025 · Melaku Alelign Mengstie, Misganaw Telake Telele · Discover Artificial Intelligence · 4

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Developing the Predictive Model for the Level of Food Insecurity Status of Households Using Ensemble Machine Learning Techniques with XAI

2024 · Melaku Mengstie · Research Square · 2

An ensemble machine learning approach for predicting anemia among under-five children in malaria-endemic sub-Saharan African countries

2026 · Berhan Tekeba, Nebebe Demis Baykemagn, et al. · Infectious Diseases of Poverty

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An ensemble machine learning approach for predicting anemia among under-five children in malaria-endemic sub-Saharan African countries

2026 · Berhan Tekeba, Nebebe Demis Baykemagn, et al. · Figshare

Predictors of self-reported sexually transmitted infections (STIs) among men in 54 low and middle income countries (LMICs): a comparison of deep learning and classical machine learning algorithms

2026 · Mequannent Sharew Melaku, Lamrot Yohannes, et al. · BMC Infectious Diseases