Digital Diagnostics

Aims & Scope

A peer-reviewed quarterly academic medical journal “Digital Diagnostics” was established in 2020.

The journal is led by prof.

V.Y.

Sinitsyn and operates under the authority of the Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department.

The journal publishes original articles presenting outcomes of clinical, experimental and fundamental studies, systematic reviews, case reports, datasets, and letters to the editor concerning live issues of the digital diagnostics.

The target audience includes scholars and health care professionals in the field of radiotherapy and clinical investigations, medical cybernetics, medical physics, information technologies, and related fields.

Metrics & Ranking

Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Directory of Open Access Journals (DOAJ)

Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Health Professions and Medicine, designed to support cutting-edge academic discovery.

Licensing & Copyright

This journal operates under an Open Access model. Articles are freely accessible to the public immediately upon publication. The content is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), allowing users to share and adapt the work with proper attribution.

Copyright remains with the author(s), and no permission is required for non-commercial use, provided the original source is cited.

Policy Links

This section provides access to essential policy documents, guidelines, and resources related to the journal’s publication and submission processes.

• Aims scope
• Homepage
• Oa statement
• Author instructions
• License terms
• Review url
• Board url
• Copyright url
• Plagiarism url
• Preservation url
• Apc url
• License

Plagiarism Policy

This journal follows a plagiarism policy. All submitted manuscripts are screened using reliable plagiarism detection software to ensure originality and academic integrity. Authors are responsible for proper citation and acknowledgment of all sources, and any form of plagiarism, including self-plagiarism, will not be tolerated.

For more details, please refer to our official: Plagiarism Policy.

APC Details

The journal’s Article Processing Charge (APC) policies support open access publishing in Health Professions and Medicine, ensuring accessibility and quality in research dissemination.

This journal does not charge a mandatory Article Processing Charge (APC). However, optional open access publication may incur fees based on the publisher’s policies.

Explore journals without APCs for alternative publishing options.

Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• MosMedData: data set of 1110 chest CT scans performed during the COVID-19 epidemic

  Citation: 91

  Authors: Sergey P., Anna E., Ivan A., Pavel B., Anna P., Alexander E., Nikolay A., Valeria Yu., Victor A.

• Evolution of research and development in the field of artificial intelligence technologies for healthcare in the Russian Federation: results of 2021

  Citation: 19

  Authors: Aleksander V., Anton V., Dariya E., Kirill M., Aleksander E.

• Methodology for testing and monitoring artificial intelligence-based software for medical diagnostics

  Citation: 19

  Authors: Yuri A., Anton V., Olga V., Kirill M., Sergey F., Denis A., Maria A.

• Reference medical datasets (MosMedData) for independent external evaluation of algorithms based on artificial intelligence in diagnostics

  Citation: 16

  Authors: Nikolay A., Anna E., Anton V., Anush A., Yury S., Sergey P.

• Chest computed tomography for outcome prediction in laboratory-confirmed COVID-19: A retrospective analysis of 38,051 cases

  Citation: 16

  Authors: Sergey P., Valeria Yu., Andreevich I., Victor A.

• Double-reading mammograms using artificial intelligence technologies: A new model of mass preventive examination organization

  Citation: 15

  Authors: Yuriy A., Ilya A., Anton V., Kirill M., Igor M., Daria D., Lev D.

• On the issue of ethical aspects of the artificial intelligence systems implementation in healthcare

  Citation: 11

  Authors: Daria E., Viktoria V., Ekaterina S., Olesia A., Anton V., Sergey P.

• Mobilizing the academic and practical potential of diagnostic radiology during the COVID-19 pandemic in Moscow

  Citation: 10

  Authors: Sergey P., Ekaterina S., Natalya V., Anton V., Irina A., Olesya A., Elena V., Anna E., Olga V., Victor A., Nikita S., Igor M., Roman V.

• Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and Elaboration. Translation to Russian

  Citation: 9

  Authors: Jan P., Erik, Douglas G., Peter C., Cynthia D., Stuart J., Charles, James J., Matthias

• Inter-observer variability between readers of CT images: all for one and one for all

  Citation: 9

  Authors: Nikolas S., Roman V., Vladimir P., Alexey B., Maxim A., Victor A., Anton V., Sergey P.