About the Journal

Stem Cell, Artificial Intelligence and Data Science Journal (SCAIDSJ) is an international, peer-reviewed, open-access scholarly journal that publishes research spanning interdisciplinary areas connecting stem cell science, artificial intelligence (AI), data science, computational methods, and technology innovation. It aims to provide a platform for original research articles, review papers, case studies, and technical reports that push the boundaries of knowledge in science, technology, and engineering, particularly where AI and data-driven approaches intersect with biological and computational research.

• The journal publishes online with Creative Commons Attribution (CC BY) open access licensing and assigns DOIs to articles.

• It follows a double-blind peer review process to ensure rigor and quality

Aims

SCAIDSJ aims to:

• Advance interdisciplinary research that integrates stem cell research with AI and data science methodologies.

• Serve as a global forum for high-quality scholarly work that addresses both theoretical foundations and practical applications.

• Promote innovative, data-driven solutions to scientific and technological challenges.

Scope of Topics

The journal welcomes submissions on a broad range of topics such as:

Core Research Themes

• Stem cell biology, regenerative medicine, and therapeutic models

• Applications of AI and machine learning in biological data analysis

• Data science methodologies for complex datasets

• Computational modeling, analytics, and bioinformatics

• Engineering applications integrating AI with biological systems

• Cross-disciplinary work combining technology, science, and engineering.

Types of Manuscripts Accepted

• Original research articles

• Review articles

• Short communications

• Case studies

• Technical reports

• Letters to the Editor

Indexing & Discoverability

Based on the journal’s site and available publication details:

• Articles are published with DOI registration, which increases visibility and citation tracking.

• The journal’s content is searchable via academic search engines like Google Scholar as typical for open-access journals (though official indexing claims are not prominently listed on the site).

At this time, SCAIDSJ does not list established indexing in major bibliographic databases such as Scopus, Web of Science, or PubMed/Medline on its official website. Authors and readers should verify current indexing directly on those platforms if required for academic evaluation or career milestones.