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Welcome to the Artificial Intelligence in Cancer

Artificial Intelligence in Cancer is an international, peer-reviewed, open-access academic journal dedicated to publishing original, high-quality research findings in the field of cancer, including clinical, translational, and basic studies. The journal focuses on, but is not limited to, the following areas: Bone oncology, breast cancer, gastrointestinal cancer, genitourinary cancer, gynecological cancer, head and neck cancer, hematologic malignancy, lung cancer, lymphoma and myeloma, pediatric oncology, and urologic oncology. Types of articles published by the journal include clinical study, basic study, case report, editorial, review, minireview, systematic review, meta-analysis, guidelines, and correspondence. All submissions undergo a rigorous and transparent peer-review process by at least two independent reviewers. Manuscripts are evaluated based on scientific rigor, originality, clinical relevance, and reproducibility, with particular attention to methodological robustness and data integrity. Constructive and timely feedback is provided to ensure the highest standards of scholarly communication. The journal adheres to the highest standards of publication ethics and editorial integrity, in accordance with the guidelines of the Committee on Publication Ethics, the International Committee of Medical Journal Editors, and the World Association of Medical Editors. To advance scientific discovery, promote evidence-based clinical practice, and foster innovation in cancer research, ultimately improving global health outcomes. We invite researchers, clinicians, and multidisciplinary experts worldwide to submit high-quality manuscripts and contribute to shaping the future of cancer science. Submit an Article >>

2025 Published Issues
1
Editors-in-Chief
  • Cédric Coulouarn, PhD, Senior Researcher, (Email: cedric.coulouarn@inserm.fr) Institut National de la Sante et de la Recherche Medicale, Univ Rennes, Rennes 35033, France
Indexing/Abstracting

The AIC is now abstracted and indexed in Reference Citation Analysis, China Science and Technology Journal Database.

Journal Metrics

There is currently no impact factor.

ISSN
2644-3228 (online)
Latest Manuscript Statistics
Received (71), Duration of Peer Review (17 days/Mean), Days from Submission to First Decision (34 days/Mean), Second Decision Time (22 days/Mean), Accepted (45.1%/Mean), Production Time (16 days/Mean), Time to Publication (73 days/Mean), and Rejected (33.8%/Mean).
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