| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Neuroscience | 131 | 135 | 103 | 21 |
| Computer Science | 366 | 52 | 63 | 16 |
The main research concerns discussed in the journal are Artificial intelligence, Pattern recognition, Neuroscience, Software and Neuroimaging. In Neuroinformatics, Machine learning and Computer vision are investigated in conjunction with one another to address concerns in Artificial intelligence research. The journal investigates Computer vision research which frequently intersects with Tracing.
Topics in Pattern recognition explored in the journal were investigated in conjunction with research in Deep learning, Diffusion MRI, Cluster analysis and Electroencephalography. The work on Neuroscience presented in it focuses on Neuroinformatics in particular. Software research featured in Neuroinformatics incorporates concerns from various other topics such as Python (programming language), Visualization, Data mining and Toolbox.
It connects research in Neuroimaging with the related topic of Magnetic resonance imaging. Specifically, studies on Image segmentation are prevalent in the Segmentation works discussed.
The most cited papers focus largely on the fields of Artificial intelligence, Neuroscience, Machine learning, Software and Neuroimaging. Issues in Artificial intelligence were discussed in the journal articles, taking into consideration concepts from other disciplines like Computer vision and Pattern recognition. The published papers hold forums on Neuroscience that merge themes from other disciplines such as Artificial neural network and Data science.
The journal investigates studies in Artificial intelligence, Pattern recognition, Neuroimaging, Convolutional neural network and Deep learning. It holds forums on Artificial intelligence that merges themes from other disciplines such as Resting state fMRI, Machine learning and Electroencephalography. The Machine learning works featured in Neuroinformatics incorporate elements from Schizophrenia (object-oriented programming), Field (computer science), Inference and Complex network.
While work presented in Neuroinformatics provided substantial information on Pattern recognition, it also covered topics in Software and Magnetic resonance imaging. Issues in Neuroimaging were discussed, taking into consideration concepts from other disciplines like Data type, Preprocessor, Grey matter, Voxel and Data science. The studies in Segmentation featured incorporate elements of Diffusion MRI and Atrophy.
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 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 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, 6.49% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 16.67% were posted by at least one author from the top 10 institutions publishing in the journal. Another 9.72% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 22.22% of all publications and 51.39% 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.
For those interested in the fascinating field of Neuroinformatics, there are several potential career paths to explore, each offering a unique way to apply the knowledge and skills acquired from the research topics noted above. Neuroinformatics combines elements of neuroscience with information science, allowing researchers and practitioners to study the brain and its functions using cutting-edge technology and complex data analysis. Those looking to apply their expertise in Neuroinformatics could consider a career as a speech-language pathologist. As a speech-language pathologist, you would utilize your knowledge of neural processes, pattern recognition, and artificial intelligence to assist individuals dealing with communication disorders. This is a rewarding career, allowing professionals to help individuals improve their speech and language abilities, in addition to their cognitive-communicative skills. To understand more about this career path and the steps to become a licensed professional in this field, particularly those residing in Arizona, you may refer to our article on how to become a speech therapist in Arizona. Another potential career pathway is becoming a data analyst in healthcare, where the skills acquired can be leveraged to interpret large datasets, analyzing the impact of different neurological conditions on patient health. Furthermore, for those inclined towards academia, a career in education is a pathway to consider. Working as a lecturer or a researcher in a university context lets you share your wealth of knowledge, perhaps inspiring the next generation of Neuroinformatics professionals. In addition to these professions, Neuroinformatics also lends itself well to several other lines of work, in both the public and private sectors. These include careers in clinical informatics, medical imaging, computational neuroscience, and neuroimaging data analysis, to name just a few. More detailed information on these career paths can be found on our research portal.
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(2021)Alessio Paolo Buccino;Alessio Paolo Buccino;Gaute Tomas Einevoll;Gaute Tomas Einevoll
(2021)Wieslaw L. Nowinski
(2021)Andrew Beers;James M. Brown;Ken Chang;Katharina Hoebel
(2021)Mathew Birdsall Abrams;Jan G. Bjaalie;Samir Das;Gary F. Egan
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