Send us your data.
Get a submission-ready manuscript in 15 days.
Raw data, tables or figures in. Statistics, interpretation, medical writing, journal submission and publication support out. Use your own dataset, or build the study from 45 open and application-based registries (SEER, NTDB, TCGA, UK Biobank and more), with ML and AI where it adds value.
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Your dataset is already a paper
Send your data; receive statistics, figures, methods, results and discussion. You stay the sole author.
Read the transcript
That dataset on your drive? It's already a paper. You collected the data. Analysis, figures, writing: that's where the months go. Editverse Just Data: send your data, and in fifteen days you get a full manuscript. Statistics, figures, methods, results and discussion. You stay the sole author, no credit asked. Every step follows your national and university ethics rules, COPE, ICMJE and GPP. See the first draft before you pay. Editverse. Data in, manuscript out.
Your data, or registry data
Your own data
Clinical, survey, lab or trial data you already hold.
- Data cleaning and statistical analysis plan
- Analysis, tables and publication-quality figures
- Methods, results and discussion written to journal style
Registry services
No dataset yet? We build the study from a registry.
- Research question and cohort definition
- Variable mapping and registry analysis (SEER, NTDB/TQP and others)
- Reporting to STROBE/RECORD standards
Full publication support
Beyond the manuscript.
- Literature review and referencing
- Journal selection and submission
- Reviewer-response support until publication
45 data sources we work with, across cancer, genetics and more
Pick a registry and we scope the study: question, cohort, variables, analysis and manuscript. Access follows each source's own terms. Where an application or data-use agreement is needed, we guide you through it.
Open download and use Registration free account or sign-up Application / licence approval or fee required
Cancer 8 sources
Genetics and genomics 13 sources
Trauma, surgery and hospital data 5 sources
Population health 9 sources
Imaging and neurology 4 sources
Asia and regional sources 6 sources
Turn registry and patient data into prediction models, not only p-values
Clinical prediction models
Risk and outcome models with logistic regression, gradient boosting and random forests, benchmarked against a simple baseline.
Survival and time-to-event ML
Cox, random survival forests and deep survival models for cancer and trauma registries.
Genomics and imaging AI
Variant and expression modelling, and deep-learning pipelines on public imaging archives.
Text and EHR mining
NLP on clinical notes and reports to build structured study datasets.
Built to be publishable. Internal and external validation, calibration, explainability (SHAP), and reporting to TRIPOD+AI. Code and analysis are handed over so your results can be reproduced.
Plan an ML studyThe data errors we find and fix before submission
Four steps, one point of contact
Share your data, aim and target journal.
You approve the analysis plan and timeline.
Full manuscript with tables and figures in 15 days.
Submission and revisions until online.
Ethics and compliance. Editverse follows COPE guidance. Ethics approval, consent and data governance follow ICMJE and the policies of your country and institution, and remain with you and your institution.
Questions
Who is the author?
You are. Editverse never asks for credit or acknowledgement.
Is my identity kept confidential?
Yes. Your identity is never disclosed to reviewers.
Which journals do you target?
SCI/E, PubMed and Scopus indexed journals across specialities, surgery included.
What if I have no data?
Use our registry services. We define the question and build the dataset from a registry.
Stop losing months to analysis and writing.
Send your dataset or your research question. You get a quote and timeline within 24 hours.
Get my free quotePlace order