Medical Data Mining
Since the beginning of the 21st century, natural science research begun to transfer from reduction to integration and from micro to macro. Life sciences and information sciences have shown a high degree of integration. It will affect the destiny and future of human beings profoundly.
Cognizing way based on macroscopic thinking is the characteristic of traditional Chinese medicine (TCM). However, the research methods of TCM that simply draw lessons from the reduction theory from western medicine were not enough. Under the background of the rapid development of bioinformatics, big data and artificial intelligence have become the concrete embodiment of the integration of modern life research and information science. They are also important tools or methods for the research of natural science, which have transferd from 'reduction and micro' to 'comprehensive and macroscopic'.
Therefore, Medical Data Mining (ISSN 2624-1587) was founded to discover the scientific laws of life and medicine through data mining and artificial intelligence, and provide a platform for publication and communication in this field.
A summary of the scope of Medical Data Mining (ISSN 2624-1587) includes:
Peer review policy
Medical Data Mining (ISSN 2624-1587) follows a double blind peer review process, to ensure impartial editorial decision-making. All submissions to Medical Data Mining (ISSN 2624-1587) are assessed by an editor, who will decide whether they are suitable for peer review. If an editor is on the author list or has any other competing interest regarding a specific manuscript, another member of the Editorial Board will be assigned to assume responsibility for overseeing peer review. Submissions felt to be suitable for consideration will be sent for peer review by appropriate independent experts. Editors will make a decision based on the reviewers’ reports and authors are sent these reports along with the editorial decision on their manuscript. Authors should note that even in light of one positive report, concerns raised by another reviewer may fundamentally undermine the study and result in the manuscript being rejected.
Authors may suggest potential reviewers if they wish; however, whether or not to consider these reviewers is at the editor's discretion. Authors should not suggest recent collaborators or colleagues who work in the same institution as themselves. Authors who wish to suggest peer reviewers can do so in the cover letter and should provide institutional email addresses where possible, or information which will help the editor to verify the identity of the reviewer.
Authors may request exclusion of individuals as peer reviewers, but they should explain the reasons in their cover letter on submission. Authors should not exclude too many individuals as this may hinder the peer review process. Please note that the editor may choose to invite excluded peer reviewers.
Intentionally falsifying information, for example, suggesting reviewers with a false name or email address, will result in rejection of the manuscript and may lead to further investigation in line with our misconduct policy.
Reviewers are therefore required to respect the confidentiality of the peer review process and not reveal any details of a manuscript or its review, during or after the peer-review process, beyond the information released by the journal. If reviewers wish to involve a colleague in the review process they should first obtain permission from the journal. The editor should be informed of the names of any individuals who assisted in the review process when the report is returned.
In 2019, Articles processing charges and submission charges are free. All accepted papers will be published free-of-charge. Moreover, Traditional Chinese Medicine Inheritance Funds will independently decide on awards which include Distinguished Contribution Award with $5,000, first prize with $2,000, second prize with $500, and third prize with certificate.