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This page outlines the journal-specific policies that govern manuscript evaluation, peer review, publication ethics, research integrity, medical artificial intelligence research, computational reproducibility, transparency and post-publication responsibilities.
These policies should be read together with ZENTIME's publisher-level Editorial Policies, Publishing Policies, and Open Access, Fees and Licensing policies. Where journal-specific requirements supplement publisher-level policies, the requirements stated on this journal website apply.
As a journal publishing research at the intersection of artificial intelligence and medicine or healthcare, the journal welcomes studies involving medical AI methods and their clinical, translational, biological or healthcare applications. Relevant areas include, but are not limited to, robotic surgery systems, disease diagnosis and prediction, medical image analysis, gene mutation prediction, medical statistics, human biology, omics technologies, simulation and prediction of treatment effects and outcomes, electronic medical records and other AI-enabled medical applications. The journal considers both methodological and application-oriented research, provided that the work has a clear and substantive relevance to medicine, healthcare or biomedical research. Research may involve nonclinical or clinical studies and may utilize in vivo, ex vivo or in vitro approaches where appropriate.
The journal expects authors, editors, reviewers and editorial board members to follow internationally recognized standards of responsible scholarly publishing, including relevant guidance from the Committee on Publication Ethics (COPE) and other applicable research integrity, data protection and responsible AI standards.
The journal operates a transparent peer review process to ensure the quality, integrity, technical rigor and scholarly value of published content.
All submitted manuscripts are first assessed by the editorial office or a handling editor for completeness, relevance to the journal’s aims and scope, ethical compliance, reporting quality, technical clarity and suitability for further evaluation. Manuscripts that are outside the journal’s scope, do not meet basic reporting standards, lack sufficient originality, contain unsupported claims or raise significant ethical, privacy, safety or security concerns may be declined before external peer review.
The journal uses a single-anonymous peer review model, in which reviewers remain anonymous to authors. Research articles, original clinical or nonclinical studies, methodological studies, methodological reviews or surveys, systematic reviews, technical studies, benchmark studies, software or algorithm papers, validation studies and other scholarly manuscripts requiring external review are normally assessed by at least two independent reviewers with relevant expertise.
For manuscripts involving medical diagnosis or prediction, medical image analysis, robotic surgery, gene mutation prediction, omics technologies, medical statistics, electronic medical records, treatment-effect prediction, human biology, clinical decision support, generative AI in healthcare or other medical AI applications, editors may invite reviewers with relevant expertise in medicine, clinical practice, artificial intelligence, machine learning, statistics, biomedical science, engineering or other appropriate disciplines.
Reviewer comments are advisory. Final editorial decisions are made by the Editor-in-Chief or designated handling editor based on editorial assessment, reviewer comments, originality, technical rigor, methodological soundness, reproducibility, ethical compliance, relevance and suitability for the journal.
Editorials, commentaries, letters, corrections and invited content may be reviewed internally or externally at the editors’ discretion, according to the nature of the content.
The journal maintains editorial independence in all editorial decisions. Decisions on individual manuscripts are made by the Editor-in-Chief, handling editors or designated editorial decision-making team in accordance with the journal’s policies.
Editorial decisions are based on scholarly merit, originality, methodological quality, technical rigor, relevance to the journal’s aims and scope, ethical integrity, reproducibility, transparency and contribution to medical artificial intelligence, medicine, healthcare or biomedical science. Decisions are not influenced by commercial interests, advertising, sponsorship, institutional affiliation, political considerations or the financial interests of ZENTIME, journal owners, editors, editorial board members, technology companies, platform providers, software vendors or any third party.
Editors and editorial board members must maintain confidentiality, declare conflicts of interest and recuse themselves from handling manuscripts where impartiality may be compromised. Manuscripts submitted by editors, editorial board members or journal staff will be handled independently by an editor without conflict of interest and will undergo the same editorial assessment and peer review standards as other submissions.
The journal is committed to maintaining high standards of publication ethics and research integrity. Authors, editors and reviewers are expected to act with honesty, transparency and accountability throughout the submission, review and publication process.
The journal does not tolerate plagiarism, redundant publication, duplicate submission, data fabrication, data falsification, image manipulation, citation manipulation, authorship manipulation, peer review manipulation, paper mills or other forms of research or publication misconduct.
For medical artificial intelligence research, authors must not misrepresent model performance, diagnostic accuracy, clinical utility, dataset provenance, benchmark results, evaluation settings, statistical significance, baseline comparisons, ablation studies, human evaluation results, annotation quality, biological interpretation, treatment-effect predictions, patient outcomes, safety findings, limitations, computational costs or sponsor involvement.
Suspected misconduct will be assessed according to the journal’s procedures and ZENTIME’s publisher-level policies. Depending on the circumstances, outcomes may include a request for clarification, manuscript rejection, correction, expression of concern, retraction, article removal or notification of relevant institutions or authorities.
All listed authors must have made substantial scholarly contributions to the work, approved the submitted version and agreed to its submission. The corresponding author is responsible for ensuring that authorship, author order, corresponding author details and required declarations have been agreed by all authors before submission.
The journal requires an author contribution statement and encourages the use of the CRediT taxonomy where appropriate. Contributors who do not meet authorship criteria should be acknowledged with their permission.
Authors must disclose all financial and non-financial competing interests that could influence, or be perceived to influence, the work. For AI research, relevant disclosures may include employment, consultancy, advisory roles, honoraria, stock ownership, patents, patent applications, licensing agreements, sponsored research, platform access, cloud credits, compute grants, dataset access, model access, software support, commercial evaluation agreements, writing assistance or other relationships with technology companies, data providers, cloud service providers, platform operators, government agencies, investors or sponsors.
All funding sources, grant numbers, institutional support, compute grants, cloud credits and in-kind support should be disclosed. Authors should state the role of funders, sponsors, technology providers or data providers in study design, data access, model development, experimental design, analysis, interpretation, manuscript preparation and the decision to submit for publication.
Authors should state whether they had full access to the data, code, model outputs and evaluation results, and whether any sponsor, platform provider, funder or commercial partner had any role in approving or restricting publication.
Changes to authorship after submission require a clear explanation, written agreement from all authors and editorial approval.
Research involving human participants, human-generated data, personal data, behavioral data, biometric data, voice data, image data, video data, location data, social media data, educational records, clinical data or other sensitive information must comply with applicable ethical, legal and data protection requirements.
Where ethics approval, institutional review board approval or exemption is required, authors should state the name of the ethics committee or review board, approval number or reference, and any relevant exemption information in the manuscript.
Informed consent should be obtained where required. Authors should describe how consent, notification, opt-out mechanisms, de-identification, anonymization, data minimization, access control and participant privacy were addressed where applicable.
Special care is required for research involving children, vulnerable groups, biometric identification, facial recognition, surveillance, emotion recognition, sensitive attributes, health data, political opinions, location tracking, social media data, scraped data, user-generated content or data collected in contexts where individuals may not reasonably expect research use.
Authors must not publish identifiable personal information, images, voice recordings, transcripts, interaction logs or other sensitive data unless publication is ethically justified, legally permitted and properly consented.
Manuscripts reporting AI research should provide sufficient information to support evaluation, interpretation and reproducibility.
Where applicable, authors should report:
model name, architecture, version and major components;
training, validation and test data sources;
dataset provenance, licensing, consent status and access conditions;
data collection, curation, annotation and quality control methods;
annotation instructions, annotator expertise and inter-annotator agreement where relevant;
preprocessing, filtering, deduplication and data cleaning procedures;
train/validation/test splits and measures taken to prevent data leakage;
baseline models and justification for comparator selection;
evaluation metrics and statistical uncertainty;
hyperparameters, optimization methods and training settings;
compute resources, hardware, software frameworks and random seeds where relevant;
ablation studies, robustness testing and sensitivity analyses where appropriate;
known limitations, failure modes and conditions under which the system should not be used.
For benchmark papers, authors should describe the benchmark design, task definitions, dataset construction, evaluation protocol, scoring methods, licensing, maintenance plan and measures to reduce contamination, overfitting or benchmark gaming.
For human evaluation studies, authors should report participant or annotator recruitment, instructions, compensation, expertise, quality control, agreement measures and ethical safeguards where applicable.
Authors should include a Data Availability Statement where applicable, describing where the data supporting the findings can be accessed or explaining why data cannot be shared.
The journal encourages authors to make code, trained models, model cards, data cards, evaluation scripts, configuration files, prompts, checkpoints, synthetic data generation procedures, annotation guidelines, experiment logs and other research artifacts available in suitable repositories where possible and appropriate.
Restrictions due to privacy, ethics, legal, commercial, intellectual property, licensing, cybersecurity, safety or misuse concerns should be clearly explained.
For computational studies, authors should provide sufficient methodological and technical detail to allow readers and reviewers to understand the system, data inputs, model outputs, experimental setup, evaluation methods, statistical analyses and limitations.
Where full release of data or models is not possible, authors should provide a clear explanation and, where appropriate, share metadata, documentation, summary statistics, evaluation code, synthetic examples or controlled access procedures.
Supplementary materials should support the main article and should not replace essential methods, results, evaluation details, dataset documentation, safety information or reproducibility materials needed to evaluate the work.
Authors should consider and report ethical, safety, security and societal implications of AI systems where relevant. This is particularly important for work involving clinical diagnosis, treatment recommendation, patient monitoring, medical decision-making, medical devices, autonomous systems, sensitive health data, autonomous decision-making, biometric identification, surveillance, cybersecurity, content generation, deception, persuasion, health, education, employment, finance, law, public services or public safety.
Where applicable, authors should discuss potential risks, limitations, foreseeable misuse, bias, fairness concerns, privacy risks, robustness failures, security vulnerabilities, environmental impact, human oversight, accountability and safeguards.
Manuscripts that provide methods, data, code, models or instructions that could enable significant harm may require additional editorial assessment. The journal may request risk mitigation, restricted disclosure, additional safeguards or clarification before peer review or publication.
Authors should avoid overstating AI system capabilities and should distinguish clearly between experimental performance, benchmark results, real-world deployment readiness and clinically, legally or socially consequential use.
AI tools and large language models cannot be listed as authors. Authors remain responsible for the accuracy, originality and integrity of all submitted content, including any content generated or assisted by AI tools.
Use of generative AI or AI-assisted technologies beyond basic language editing should be disclosed in the manuscript according to the journal’s requirements. Authors should identify the tool used, the purpose of use and the section or content affected where appropriate.
AI tools must not be used to fabricate, falsify or manipulate data, images, references, citations, peer review materials, experimental results, model outputs, evaluation scores, clinical recommendations, patient information or conclusions.
Authors should verify all AI-assisted content, including references, code, mathematical statements, factual claims and generated text. Fabricated references, unverifiable claims or misleading AI-generated content may be treated as publication ethics concerns.
Editors and reviewers must not upload confidential manuscripts, peer review reports, decision letters or related materials to public AI tools unless explicitly permitted by the journal and consistent with confidentiality and data protection requirements.
The journal considers manuscripts that have been posted as preprints, provided that the work has not been formally published and is not under consideration by another journal at the same time.
Authors must disclose any preprint, conference paper, workshop paper, technical report, thesis, white paper, software documentation, dataset documentation, model release note, blog post or related prior dissemination at submission. Where applicable, authors should provide the preprint server name, DOI, repository link or conference citation.
Authors should clearly explain the relationship between the submitted manuscript and any prior version, including what is new in the submitted work. Duplicate submission and redundant publication are not permitted.
If the manuscript is accepted, authors are encouraged to update the preprint or repository record with a citation and link to the final published article.
Open Access
The journal is a Gold Open Access journal. All published articles are freely and permanently available online immediately upon publication.
Authors should review the journal's Open Access and Fees page before submission for information on article processing charges, waiver or discount options, copyright, licensing, article sharing and self-archiving.
Copyright
Authors are required to transfer copyright in their accepted manuscript to the journal upon acceptance for publication.
In exceptional circumstances, including where specific institutional or funder requirements apply, authors may contact the editorial office to discuss alternative copyright arrangements.
Licensing
All published articles are licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.
The CC BY 4.0 license permits others to share, copy, redistribute, remix, transform and build upon the work for any purpose, including commercially, provided that appropriate credit is given to the original authors and source, a link to the license is provided, and any changes are indicated.
Article Sharing and Self-Archiving
Authors may share, host and self-archive the published Version of Record in accordance with the CC BY 4.0 license.
Articles may be shared through institutional repositories, personal websites, academic networks and other appropriate platforms, provided that appropriate attribution to the original publication is retained and the terms of the CC BY 4.0 license are respected.
Use of Third-Party and Previously Published Material
Authors are responsible for obtaining permission to reproduce or adapt material owned by third parties where permission is required. This includes material previously published by the authors themselves if the copyright is held by another publisher or third party.
Permission may be required for, including but not limited to:
previously published figures, tables, graphs, charts, schemes, artworks or other content that is reproduced or only slightly modified;
substantial extracts of text or other material from previously published works;
photographs, images or other visual materials for which the authors do not hold the necessary rights; and
the authors' own previously published material where the authors have not retained the relevant copyright or reuse rights.
Authors should obtain all necessary permissions before submitting the manuscript and provide appropriate attribution and permission statements where required.
Authors are responsible for ensuring that the use of third-party material complies with applicable copyright, license and permission requirements. Third-party material may not necessarily be covered by the CC BY 4.0 license applied to the article as a whole.
The journal is committed to maintaining the integrity and transparency of the scholarly record. Post-publication updates may include corrections, expressions of concern, retractions or article removal where appropriate.
Corrections may be issued for significant errors that do not invalidate the article. Retractions may be issued when findings are unreliable, unethical or substantially compromised. Expressions of concern may be issued when serious concerns remain unresolved.
For AI research, post-publication concerns may include unreliable benchmark results, undisclosed data leakage, invalid evaluation protocols, fabricated or manipulated data, undisclosed conflicts of interest, misrepresented model capabilities, privacy breaches, unsafe release of harmful models or code, fabricated references, unverifiable claims or other issues that may affect scholarly, technical or societal interpretation.
Authors may appeal an editorial decision or submit a complaint by contacting the Editorial Office. Appeals should identify specific concerns, such as a possible error in the editorial process, a misunderstanding of the manuscript or evidence that relevant information was not adequately considered.
Appeals do not guarantee reconsideration, external review or reversal of the original decision. Repeated appeals without new evidence may not be considered. Complaints regarding editorial conduct, peer review, conflicts of interest, confidentiality or publication ethics will be handled fairly, confidentially and in a timely manner.
Related ZENTIME publisher policies:
Editorial Policies
Publishing Policies
Open Access, Fees and Licensing
Related external standards and resources may include:
Committee on Publication Ethics
FAIR Principles
DataCite
Creative Commons
CRediT Taxonomy
Model Cards
Data Cards
Datasheets for Datasets
Relevant community reproducibility checklists and responsible AI guidelines
