The Babylonian Journal of Machine Learning (BJML) (EISSN: 3006-5429) is a specialized publication dedicated to the exploration and integration of modern machine learning methodologies. As a platform for researchers and scholars, the journal focuses on the intersection of cutting-edge advancements in machine learning. Through high-quality articles, it fosters interdisciplinary discussions aimed at propelling forward the field of machine learning research.

Current Issue

Vol. 2025 (2025)

In Progress

Published: 2025-01-10

Articles

Integrating Machine Learning and Genetic Algorithms to Enhance Gene-Disease Classification: An XBNet-Based Framework

Rana Khalid Hamad

1-12

PDF
DOI: https://doi.org/10.58496/BJML/2025/001

Analysis of the performance of algorithms (K-Means, Farthest First, Hierarchical) Using the data analysis and modeling tool Weka

Mohammed Basil Abdulkareem

13-26

PDF
DOI: https://doi.org/10.58496/BJML/2025/002

A Bibliometric Analysis of Segment Anything (SA) Research: Global Trends, Key Contributors, and Thematic Insights

Fredrick Kayusi , Rubén González Vallejo , Linety Juma , Michael Keari Omwenga , Petros Chavula

27-41

PDF
DOI: https://doi.org/10.58496/BJML/2025/003

Enhancing Semantic Image Retrieval Using Self-Supervised Learning: A Label-Efficient Approach

Malik Sallam , Marwan Ali Shnan

42-60

PDF
DOI: https://doi.org/10.58496/BJML/2025/004

The Global Landscape of Technology-assisted English Language Teaching Research: A Bibliometric Analysis

Sara S. Alnakeeb , Eslam Hossam , Ramy Aldallal , Omega John Unogwu , Gertrude Milat

61-75

PDF
DOI: https://doi.org/10.58496/BJML/2025/005

Privacy-Preserving Transfer Learning for Community Detection in Multiple Networks: A Review.

Marshima Mohd Rosli

76-85

PDF
DOI: https://doi.org/10.58496/BJML/2025/006

Enhancing Governmental Decision-Making through Predictive Analytics with Machine Learning-Based Data-Driven Framework

Mahdi Salah Mahdi AL-Inizi

86-96

PDF
DOI: https://doi.org/10.58496/BJML/2025/007
View All Issues