International Journal of AI, Machine Learning & Data Science (IJAIMLDS)

IJAIMLDS follows a double-blind peer review process to ensure fairness, objectivity, and academic quality.

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Review Model

• Double-blind review: authors and reviewers do not know each other’s identities
• At least two independent reviewers evaluate each submission
• Additional reviewers may be invited when required

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Selection of Reviewers

• Reviewers are selected based on subject expertise and research experience
• Reviewers with conflicts of interest are not assigned
• Authors may suggest reviewers, but the editors are not obliged to use them

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Review Criteria

Reviewers evaluate submissions based on:

• Originality and significance of the research
• Technical quality, rigor, and clarity
• Appropriateness of research methods
• Quality and accuracy of results and interpretation
• Contribution to the fields of AI, machine learning, and data science
• Proper citation and ethical integrity

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Editorial Decisions

After receiving reviewer reports, the editor may decide:

• Accept
• Minor revisions required
• Major revisions required
• Reject

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Revisions

• Authors must respond to each reviewer comment in a structured response document
• Revised manuscripts may be sent for additional review if needed

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Confidentiality

• All manuscripts, reviews, and editorial communications are confidential
• Reviewers must not share or use manuscript content for personal research

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Misconduct

• Cases of plagiarism, data fabrication, or unethical research practices result in rejection
• Severe cases may lead to author blacklisting or institutional notification

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IJAIMLDS is committed to maintaining the highest standards of ethical and rigorous peer review.