Peer Review Process

Peer Review Process

The Journal Draft – AI in Medicine follows a rigorous and transparent double-blind peer review system to ensure the publication of high-quality, reliable, and ethical scientific work. Our review process is designed to uphold scientific integrity, maintain fairness, and promote reproducibility in AI-driven healthcare research.

1. Double-Blind Peer Review

To maintain impartiality and eliminate bias:

  • The identities of authors are hidden from reviewers.

  • The identities of reviewers are hidden from authors.

  • Manuscripts are reviewed solely based on scientific merit, originality, clarity, and ethical standards.

Authors must ensure their submissions are free of identifying information in the manuscript file and supplementary materials.

2. Initial Editorial Screening

Every submitted manuscript undergoes a preliminary assessment by the Editor-in-Chief or a designated Associate Editor. During this stage, the manuscript is evaluated for:

  • Relevance to the journal’s aims and scope

  • Adherence to submission guidelines

  • Ethical compliance and AI transparency

  • Basic scientific and linguistic quality

Manuscripts that do not meet these criteria may be returned to authors for revision or declined without external review.

3. Assignment to Independent Expert Reviewers

Manuscripts that pass initial screening are sent to a minimum of two independent expert reviewers with subject expertise relevant to the manuscript’s focus area.

Reviewer selection is based on:

  • Field specialization

  • Research experience

  • Absence of conflicts of interest

  • Prior review quality and responsiveness

External reviewers provide anonymous, unbiased feedback through a standardized evaluation form.

4. Specialized Statistical or Methodological Review

For manuscripts involving advanced algorithms, machine learning models, or complex statistical methods, an additional statistical or methodological review may be required.

This ensures:

  • Proper model validation

  • Correct use of statistical techniques

  • Reproducibility of computational workflows

  • Transparency of AI methods and performance metrics

Technical papers may be evaluated by experts in data science, biostatistics, algorithmic design, or computational medicine.

5. Reproducibility Requirements

To promote transparent and verifiable scientific research, authors may be asked to provide:

  • Source code or scripts

  • Model parameters and architectures

  • Datasets (public or anonymized when applicable)

  • Detailed computational workflows

These materials may be submitted as supplementary files or through secure repositories. Confidential patient data must be fully anonymized and ethically compliant.

6. Reviewer Recommendations & Editorial Decision

After receiving reviewer reports, the editor synthesizes feedback and makes one of the following decisions:

  • Accept

  • Minor Revision

  • Major Revision

  • Resubmit for Review

  • Reject

Authors receive consolidated and anonymized reviewer comments along with clear revision instructions.

Revised manuscripts may undergo further rounds of review depending on the extent of changes required.

7. Final Acceptance & Pre-Publication Checks

When a manuscript is accepted, it proceeds to:

  • Plagiarism screening

  • Ethical compliance verification

  • Formatting and reference checking

  • Proofreading and author proof approval

Once finalized, the article is scheduled for publication in the appropriate issue.

8. Post-Publication Policies

Published articles may undergo corrections, updates, or retractions if significant errors or ethical concerns are identified. We follow COPE (Committee on Publication Ethics) guidelines for all post-publication actions.