Rigorous, reproducible research at the intersection of AI and medicine.
Vallensis Publishing is a Switzerland-based open-access publisher for biomedical artificial intelligence. Every submission passes a transparent, automated technical-integrity screening before double-blind peer review — so the science we publish stands up to scrutiny.
Publication ethics policies aligned with COPE guidance (membership application submitted) · DOI registration via Crossref (membership application submitted) · Open access under CC BY 4.0.
Why Vallensis
Integrity · Rigour · OpennessTechnical integrity first
Every submission passes automated integrity screening — scope fit, figure quality, statistical reporting, data availability — before peer review.
35-day target to first decision
Structured reviewer coordination and priority handling support faster turnaround — without compromising rigour. The 35-day figure is a target median, not a guarantee.
Switzerland-based, globally open
Published under CC BY 4.0 — fully open access, no subscription barriers, with long-term preservation.
Two founding journals
Founding Collection · openJournal of Privacy-Preserving AI in Medicine
Federated learning, differential privacy and secure computation that let clinical AI learn without exposing patient data.
Journal of AI-Driven Drug Discovery
Generative molecular design, protein structure prediction and AI methods across the drug-discovery pipeline.
Founding Collection — open for submissions.
We are building the founding collection of each journal. Contributions accepted during this phase are published with a full APC waiver and receive priority editorial handling:
- Full APC waiver — no publication charge
- Priority handling — target median: 35 days to first decision
- An optional, author-approved graphical abstract in the journal's style
- Front-page visibility in the Founding Collection
Built on trust
What every paper undergoesBefore peer review, every manuscript is checked for scope fit, reporting-standard compliance, statistical reporting, figure quality, data & code availability and double-blind integrity. Read the Technical Integrity Standard →