| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Neuroscience | 162 | 119 | 108 | 18 |
Frontiers in Neuroinformatics aims to foster the development of research in Artificial intelligence, Neuroscience, Pattern recognition, Machine learning and Software. The journal focuses on Artificial intelligence but the discussions also offer insight into other areas such as Neuroimaging, Data mining and Computer vision. The studies tackled, which mainly focus on Neuroimaging, apply to Data science as well.
Frontiers in Neuroinformatics is focused mainly on Neuroscience, particularly Neuroinformatics. Issues in Software were discussed, taking into consideration concepts from other disciplines like Python (programming language) and Visualization. In Frontiers in Neuroinformatics, researchers investigate the Python (programming language) study as part of research in the field of Programming language.
The most cited papers primarily tackle Artificial intelligence, Python (programming language), Software, Data mining and Machine learning. In addition to Artificial intelligence research, the most cited publications aim to explore topics under Diffusion MRI, Neuroimaging and Pattern recognition. While the journal publications focused on Python (programming language), they were also able to explore topics like Data science, Visualization, Scripting language and Computational neuroscience.
The main research concerns discussed in Frontiers in Neuroinformatics are Artificial intelligence, Pattern recognition, Machine learning, Neuroimaging and Artificial neural network. Software and Functional magnetic resonance imaging are some topics wherein Artificial intelligence research discussed in the journal have an impact. Pattern recognition research featured in Frontiers in Neuroinformatics incorporates concerns from various other topics such as Supervised learning, Brain morphometry, Brain mapping and Statistical parametric mapping.
Frontiers in Neuroinformatics explores research in Stroke and overlapping concepts in Open data, Informatics and Medical physics to expand the discourse in Neuroimaging. The Artificial neural network works featured in Frontiers in Neuroinformatics incorporate elements from Python (programming language), Speaker recognition, Voice analysis and Telephone network. The close relationship between Object (computer science) and Toolbox is one of the points of interest dissected in Python (programming language) research.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in Frontiers in Neuroinformatics (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in Frontiers in Neuroinformatics (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 3.57% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 18.52% were posted by at least one author from the top 10 institutions publishing in the journal. Another 1.85% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 11.11% of all publications and 68.52% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
While delivering highly educational and insightful articles, Frontiers in Neuroinformatics, through its research initiatives, also opens up numerous career pathways in the field for aspiring professionals. Professionals with an area of interest in neuroscience and related fields can pursue various opportunities, from academic research to practical applications involved in treating neurological disorders. One such career path entails becoming a Speech-Language Pathologist, a specialty that could leverage Neuroinformatics research to improve clinical outcomes. Earning an texas slp license requirements creates an opportunity to impact the lives of patients suffering from communication and swallowing disorders. Other potential career paths include roles such as Neuroinformaticians, Neuroimaging Analysts, and Machine Learning Engineers, all of which contribute to the further development of frontiers in this multidisciplinary field. Qualified individuals can also contribute to scientific academia, enhancing our understanding of the brain and nervous system. In conclusion, the expansion of the Neuroinformatics field results not just in the advancement of our scientific understanding, but also in the creation of viable, impactful careers for interested individuals. Hence, budding researchers and professionals should monitor developments in this sector and consider these promising career paths.
Gloria Castellazzi;Gloria Castellazzi;Maria Giovanna Cuzzoni;Matteo Cotta Ramusino;Daniele Martinelli
(2020)Francesca Mandino;Francesca Mandino;Domenic H. Cerri;Clement M. Garin;Clement M. Garin;Milou Straathof
(2020)Tomi Karjalainen;Jouni Tuisku;Severi Santavirta;Tatu Kantonen
(2020)Nicolaas E. Groeneboom;Sharon C. Yates;Maja A. Puchades;Jan G. Bjaalie
(2020)Ada Johanne Ellingsrud;Andreas Våvang Solbrå;Gaute Einevoll;Gaute Einevoll;Geir Halnes;Geir Halnes
(2020)Philippe Boutinaud;Ami Tsuchida;Alexandre Laurent;Filipa Adonias
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