About
Table of Contents
Aims and scope
BMC Artificial Intelligence is an open access, peer-reviewed journal that provides an interdisciplinary platform for artificial intelligence (AI) research within the life, biological and medical sciences. Research areas considered include machine learning and intelligence, methodological advances in AI, and AI ethics and regulations. There is also a focus on life sciences and medical AI applications including pharmacology and drug development, diagnostics and precision medicine, medicinal chemistry, and agricultural and environmental sciences.
Aligned with the objectives of the United Nations Sustainable Development Goals, BMC Artificial Intelligence particularly encourages papers focused on good health and well-being (SDG3) , quality education (SDG 4), clean water and sanitation (SDG6), industry, innovation, and infrastructure (SDG 9), sustainable cities and communities (SDG 11), responsible consumption and production (SDG 12), Climate Action (SDG 13), and life on land (SDG 15). It also promotes research that introduces innovative perspectives on AI challenges and applications, and shows the importance and success of their implementation in the modern world.
Open access
All articles published by BMC Artificial Intelligence are made freely and permanently accessible online immediately upon publication, without subscription charges or registration barriers. Further information about open access can be found here.
As authors of articles published in BMC Artificial Intelligence you are the copyright holders of your article and have granted to any third party, in advance and in perpetuity, the right to use, reproduce or disseminate your article according to the licence terms.
For those of you who are US government employees or are prevented from being copyright holders for similar reasons, BMC can accommodate non-standard copyright lines. Please contact us if further information is needed.
Data availability policy
Back to topBMC Artificial Intelligence follows the policies of the BMC journals, unless otherwise noted below which are designed to support our commitment to open data sharing.
Availability of datasets
Where a widely established research community expectation for data archiving in public repositories exists, submission to a community-endorsed, public repository is mandatory. A list of data where deposition is required, can be found on the Editorial Policies Page.
BMC Artificial Intelligence strongly encourages that all datasets on which the conclusions of the paper rely should be available to readers. We encourage authors to ensure that their datasets are either deposited in publicly available repositories (where available and appropriate) or presented in the main manuscript or additional supporting files whenever possible. If a dataset is not able to be deposited in any of the above repositories due to legal guidelines or ethical reasons, this must be clearly stated in the “Availability of Data and Materials” section.
Data citation
BMC endorses the Force 11 Data Citation Principles and requires that all publicly available datasets be fully referenced in the reference list with an accession number or unique identifier such as a digital object identifier (DOI).
Authors are required to formally cite any datasets stored in external repositories that are mentioned within their manuscript, including the main datasets that are the focus of the submission, as well as any other datasets that have been used in the work. For previously published datasets, we ask authors to cite both the related research articles and the datasets themselves. All methods, software, and code developed for the manuscript should include a citation on the reference list.
All Springer Nature journals, including BMC Artificial Intelligence, are participants in the Initiative for Open Citations. As such, data citations are included in full in the formal reference list, exported to Crossref and are openly available.
An author list and title for the dataset should be included in the data citation, and should reflect the author(s) and dataset title recorded at the repository. If author or title is not recorded by the repository, these should not be included in the data citation. The name of the data-hosting repository, URL to the dataset and year the data were made available are required for all data citations. For DOI-based (e.g. figshare or Dryad) repositories the DOI URL should be used. For repositories using accessions (e.g. SRA or GEO) an identifiers.org URL should be used where available. Please refer to the following examples of data citation for guidance:
- Zhang, Q-L., Chen, J-Y., Lin, L-B., Wang, F., Guo, J., Deng, X-Y. Characterization of ladybird Henosepilachna vigintioctopunctata transcriptomes across various life stages. figshare https://doi.org/10.6084/m9.figshare.c.4064768.v3 (2018).
- NCBI Sequence Read Archive https://identifiers.org/ncbi/insdc.sra:SRP121625 (2017).
- Barbosa, P., Usie, A. and Ramos, A. M. Quercus suber isolate HL8, whole genome shotgun sequencing project. GenBank https://identifiers.org/ncbi/insdc:PKMF00000000 (2018).
- DNA Data Bank of Japan https://trace.ddbj.nig.ac.jp/DRASearch/submission?acc=DRA004814 (2016).
Availability of computer code and software
Authors must make available upon request, to editors and reviewers, any previously unreported custom computer code or algorithm used to generate the data presented in the manuscript. If published, the software application/tool should be readily available to any scientist wishing to use it for non-commercial purposes, without restrictions (such as the need for a material transfer agreement). If the implementation is not made freely available, then the manuscript should focus clearly on the development of the underlying method and not discuss the tool in any detail.
A statement describing how software or custom code can be accessed must be included in the Declaration section “Availability of Data and Materials". License information for the software or method should also be stated clearly in the “Availability of Data and Materials section” and on the repository site.
This section should include a link to the most recent version of your software or code (e.g. GitHub or Sourceforge or Code Ocean) as well as a link to the archived version referenced in the manuscript. The software or code should be archived in an appropriate repository with a DOI or other unique identifier. For software in GitHub, we recommend using Zenodo.
Code with an assigned DOI must be formally cited and listed in the References section of the manuscript.
Availability of research materials
BMC Artificial Intelligence follows the BMC editorial policies for the sharing of research materials.
Submission of a manuscript to a BMC journal implies that materials described in the manuscript, including all relevant raw data, will be freely available to any scientist wishing to use them for non-commercial purposes. It is acceptable to request reasonable payment to cover costs of distribution and reagents may be made available via commercial or non-commercial third party providers. Any restrictions on materials availability, including if materials are to be distributed by a for-profit company, must be clearly stated in the paper. As per our policy on authorship responsibilities, it is expected that the corresponding author (or relevant designated authors) will be responsible for materials availability unless otherwise stated.
Study pre-registration
BMC Artificial Intelligence encourages study pre-registration and pre-registration of analysis plans in public repositories; details of pre-registration should be provided in the manuscript.
Replication studies
BMC Artificial Intelligence welcomes submission of replication studies that provide new insights into previously published results and will evaluate these submissions with the same editorial standards we apply to other submissions.
Standards of reporting
BMC Artificial Intelligence advocates complete and transparent reporting of research and follows the BMC editorial policies on standards of reporting. Additional information is available through the journal’s submission guidelines.
Helpful resources for sharing your research data
We are committed to supporting researchers in sharing their research data, and getting the credit they deserve. Here are some useful resources to help:
- Get free advice from our research data help desk
- Find a recommended repository for your data
- Publish your data in BMC Genomic Data (genomic, transcriptomic and high-throughput genotype data) or in BMC Research Notes (data from across all natural and clinical sciences)
Article processing charges (APC)
Authors who publish open access in BMC Artificial Intelligence are required to pay an article processing charge (APC). The APC price will be determined from the date on which the article is accepted for publication.
The current APC, subject to VAT or local taxes where applicable, is: £1490.00/$1990.00/€1690.00*
*This journal is part of Springer Nature’s country-tiered APC pricing pilot. Find out more about the APC applicable to your country.
Visit our open access support portal and our Journal Pricing FAQs for further information.
Open access funding
Visit Springer Nature’s open access funding & support services for information about research funders and institutions that provide funding for APCs.
Springer Nature offers agreements that enable institutions to cover open access publishing costs. Learn more about our open access agreements to check your eligibility and discover whether this journal is included.
Requests for APC waivers and discounts from authors will be considered on a case-by-case basis, and may be granted in cases of financial need (see our open access policies for journals for more information). All applications for discretionary APC waivers and discounts should be made at the point of manuscript submission; requests made during the review process or after acceptance are unable to be considered.
Indexing services
The full text of all articles is deposited in digital archives around the world to guarantee long-term digital preservation. You can also access all articles published by BioMed Central on SpringerLink.
We are working closely with relevant indexing services including PubMed Central and Web of Science (Clarivate Analytics) to ensure that articles published in BMC Artificial Intelligence will be available in their databases when appropriate.
Peer-review policy
Peer-review is the system used to assess the quality of a manuscript before it is published. Independent researchers in the relevant research area assess submitted manuscripts for originality, validity and significance to help editors determine whether the manuscript should be published in their journal. You can read more about the peer-review process here.
Collections and Special issues
All articles submitted to Collections and Special issues are peer reviewed in line with the journal’s standard peer review policy and are subject to all of the journal’s standard editorial and publishing policies. This includes the journal’s policy on competing interests. The Editors declare no competing interests with the submissions which they have handled through the peer review process. The peer review of any submissions for which the Editors have competing interests is handled by another Editor who has no competing interests.
Editorial policies
All manuscripts submitted to BMC Artificial Intelligence should adhere to BMC's editorial policies.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appeals and complaints
Authors who wish to appeal a rejection or make a complaint should follow the procedure outlined in the BMC Editorial Policies.
Benefits of publishing with BMC
High visibility
BMC Artificial Intelligence's open access policy allows maximum visibility of articles published in the journal as they are available to a wide, global audience.
Speed of publication
BMC Artificial Intelligence offers a fast publication schedule whilst maintaining rigorous peer review; all articles must be submitted online, and peer review is managed fully electronically (articles are distributed in PDF form, which is automatically generated from the submitted files). Articles will be published with their final citation after acceptance, in both fully browsable web form, and as a formatted PDF.
Flexibility
Online publication in BMC Artificial Intelligence gives you the opportunity to publish large datasets, large numbers of color illustrations and moving pictures, to display data in a form that can be read directly by other software packages so as to allow readers to manipulate the data for themselves, and to create all relevant links (for example, to PubMed, to sequence and other databases, and to other articles).
Promotion and press coverage
Articles published in BMC Artificial Intelligence are included in article alerts and regular email updates. Some may be highlighted on BMC Artificial Intelligence’s pages and on the BMC homepage.
In addition, articles published in BMC Artificial Intelligence may be promoted by press releases to the general or scientific press. These activities increase the exposure and number of accesses for articles published in BMC Artificial Intelligence. A list of articles recently press-released by journals published by BMC is available here.
Copyright
As an author of an article published in Cancer & Metabolism you retain the copyright of your article and you are free to reproduce and disseminate your work. For further information, see our guide to licensing, copyright and author rights.
For further information about the advantages of publishing in a journal from BMC, please click here.