About the Journal
Web3 Journal: ML in Health Science
AIM AND SCOPE:
Web3 Journal: ML in Health Science is a non-profit, peer-reviewed (single-blind) online journal that publishes research AI, ML, E-Health, the Metaverse, and Web3, which enhances human well-being and is compliant with current healthcare standards.
The Journal offers Web3 Diamond Open Access, which rewards contributing authors and reviewers with Web3 assets and ensures no fees. The peer review process is based on recommendations for authors and their projects, which the editorial board regularly updates for improvements:
COPYRIGHT:
All accepted articles are published immediately after production, ensuring quick access and immediate citation for authors and readers. Content is freely and unrestrictedly available to everyone under the Creative Commons Attribution 4.0 International (CC BY) license BY-SA. Authors retain the copyright and full publishing rights without restrictions. Our journal allows authors the flexibility to deposit versions of their work in an institutional or other repository of their choice, supporting wider dissemination and accessibility of their research.
PUBLISHING SHEDULE:
The journal publishes one issue per year, with the exception of the inaugural issue, which was published outside the regular schedule.
INDEXING AND ARCHIVING:
The Journal is a member of Crossref. All publications are automatically listed on the following platforms:
- WorldCat
- Scilit
- ResearchGate
- ORCID
The journal content is automatically preserved in the PKP Preservation Network. The journal regularly performs backups of its content on its own secured storage to ensure the safety and permanence of published works. Additionally, all publications on original projects will be archived in our blockchain repository.
LANGUAGE:
The manuscripts are published in English. However, we welcome manuscripts in any language! Publications undergo professional translation by Lingrowth, an international language service provider specializing in medical and life science translations. Both the translation and publication in our journal are offered at no cost to the authors!
MANUSCRIPT SELF-CREATION SERVICE:
If you have a project but are new to the field of academic publishing and are looking for assistance, you can utilize our tools for manuscript self-creation. Simply fill in the forms provided under the links and submit: Manuscript Self-Creator
EDITING OF PUBLISHED ARTICLES:
We allow editing of published content. Minor edits will be performed within the same version and DOI of publication. Major edits will be performed within the same DOI, with the new version superseding the previous one. Authors should contact the editorial board to request editing of their published papers.
WEB3 ACADEMIC PUBLISHING:
The Journal utilizes a unique Hybrid Object Identification (HOI) for publications with DOIs and Blockchain. This method leverages the security, transparency, and immutability of Blockchain technology and incorporates automatic indexing of published content in academic databases.
The Smart Contract on the BNB blockchain serves as a unique identifier for the journal, similar to the centralized ISSN system: 0x724C2fB83d76ebc8667b326988c173D6D6d20549
The MLHS governance Token, built on the BNB Blockchain, secures decentralized identification for human-centered AI, ML, E-Health, and Web3 projects, and acts as a reward mechanism for contributing authors and reviewers, while providing Web3 Diamond Open Access.
Publications describing original, human-centered AI, ML, E-Health, Metaverse, and Web3 projects will be added to our blockchain award repository:
COLLABORATE WITH US:
We warmly invite you to collaborate with us. Whether you're a researcher eager to publish your manuscript with Web3 Diamond Open Access and Hybrid (Blockchain + DOI) identification, an industry professional seeking medical and ethical guidance for your ML, AI, E-Health, Metaverse, or Web3 project, a scientist interested in joining our board, or a developer aspiring to create your own Web3 Journal, you are welcome at ML in Health Science.
Submit Your Research: Sign in
Or simply contact us here: Contact
