Journal Impact Factor: 0.71*
Index Copernicus Value: 80.53
British Journal of Research (2394-3718) is an international quarterly open access journal which aims to publish articles related to different research fields and specialities. The focus of the journal will be to provide a platform for excellent quality research, discussion and output of work in the following areas: General Medical, Pharmacy, Economics, Agriculture, Arts, Engineering, Education, Social Science, etc.
To ensure academic constancy, the journal performs a blind peer review process.
Submission for review is expected to be at a level whereby the Editorial Board think it would be of interest to an international readership.
The scope of this journal is to:
• Publish evidence-based information.
• Dissemination of clinical experience.
• Focus on innovative and topical research.
• Ensure that a robust design and analysis if fundamental to any work submitted.
Open Access Statement
This is an open access Journal which means that all content is freely available without charge to the user or his/her institution. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other lawful purpose, without asking prior permission from the publisher or the author. This is in accordance with the BOAI definition of open access.
*2017 Journal Impact Factor was established by dividing the number of articles published in 2015 and 2016 with the number of times they are cited in 2017 based on Google Scholar Citation Index database. If 'X' is the total number of articles published in 2015 and 2016, and 'Y' is the number of times these articles were cited in indexed journals during 2017 then, impact factor = Y/X
Author(s): Jean-Marc Guichet, Patrick Frayssinet, Jean-Marc Virion, Luca Petruccio Piodi, Carmelo Messina and Fabio Massimo Ulivieri
Bone function requires a good repair system. The quantitative role of each healing component, mainly periosteum and bone marrow/endosteum and of their interactions is not clearly known. To evalu ... Read More
Author(s): Gloria Bonaccorsi, Carlo Cervellati, Enzo Grossi, Enrica Fila, Leo Massari, Nicola Veronese, Francesco Pio Cafarelli, Giuseppe Guglielmi
Artificial neural networks (ANNs) are a computational tool, based on highly non-linear mathematics models with potential applications in the prediction of osteoporotic fractures. Therefore, the ... Read More
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