PEER REVIEW PROCESS

All papers submitted to the proceedings “Opportunities and Challenges in the Development of AI-Based Public Health” undergo a scientific peer review process to ensure academic quality, thematic relevance, and scientific integrity in the field of AI-based Public Health.

Each paper is reviewed by at least two reviewers with expertise relevant to the manuscript topic, such as public health, epidemiology, health information systems, bioinformatics, health data science, and the application of AI in public health services. Reviewers assess the originality, methodology, scientific contribution, ethical aspects, and relevance of the paper to the theme of the proceedings.

The review process is conducted using a double-blind review method, in which the identities of both authors and reviewers are concealed to ensure objective and unbiased evaluation. Reviewers are given a specified period to complete one round of review, and their assessments are used by the editor or scientific committee as the basis for decision-making.

If revisions are required, authors must revise their manuscripts by systematically addressing all comments and recommendations provided by the reviewers. The editor or scientific committee will verify the revised manuscript before making a final decision on acceptance.

The entire peer review and manuscript management process is conducted online through the proceedings management system or platform designated by the organizer, while upholding the principles of transparency, confidentiality, and ethical standards of scholarly publication.