1746-8094
Published by: Elsevier
https://www.journals.elsevier.com/biomedical-signal-processing-and-control
| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Electronics and Electrical Engineering | 156 | 91 | 132 | 22 |
The topics of Artificial intelligence, Pattern recognition, Electroencephalography, Speech recognition and Signal are the focal point of discussions in Biomedical Signal Processing and Control. Biomedical Signal Processing and Control focuses on Artificial intelligence research which is adjacent to topics in Computer vision. The journal addresses concerns in Pattern recognition which are intertwined with other disciplines, such as Artificial neural network, Deep learning, Brain–computer interface and Feature (computer vision).
It features studies on Brain–computer interface, including topics such as Motor imagery. More specifically, the research on Signal in Biomedical Signal Processing and Control is related to Noise (signal processing). Segmentation works presented in the journal have a specific focus on Image segmentation.
The most cited publications primarily tackle Artificial intelligence, Pattern recognition, Speech recognition, Computer vision and Support vector machine. The journal papers address concerns in Artificial intelligence which are intertwined with other disciplines, such as Machine learning and Electroencephalography. Pattern recognition study tackled in the most cited articles is connected to the field of Hilbert–Huang transform.
Biomedical Signal Processing and Control mainly deals with areas of study such as Artificial intelligence, Pattern recognition, Segmentation, Deep learning and Convolutional neural network. The study on Artificial intelligence presented in Biomedical Signal Processing and Control intersects with the topics under Machine learning. Feature selection is a focus of the Pattern recognition works in it.
The journal explores research in Feature selection and the adjacent study of Support vector machine. Research on Segmentation addressed in it frequently intersections with the field of Pixel. It investigates Deep learning research which frequently intersects with Computed tomography.
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 Biomedical Signal Processing and Control (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 Biomedical Signal Processing and Control (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 2022 edition, 13.42% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 11.63% were posted by at least one author from the top 10 institutions publishing in the journal. Another 6.98% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 10.08% of all publications and 71.32% 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.
Georgios Petmezas;Kostas Haris;Leandros Stefanopoulos;Vassilis Kilintzis
(2021)Adyasha Rath;Debahuti Mishra;Ganapati Panda;Suresh Chandra Satapathy
(2021)Priyadarshiny Dhar;Saibal Dutta;Vivekananda Mukherjee
(2021)Pursuing a degree in Computer Science in the USA opens up numerous opportunities both academically and professionally. For those interested in advanced study, exploring online PhD programs can be a flexible way to achieve the highest level of expertise without relocating or interrupting your career.
If a quicker path is preferred, there are many online masters degree options tailored to enhance skills in less than two years. This is ideal for professionals looking to upskill or pivot within the tech industry efficiently.
Choosing the right program also involves considering job prospects. Some degrees are listed among the highest paying online degrees, highlighting the financial benefits of certain career tracks in computer science-related fields.
Looking ahead, it’s wise to focus on programs identified as the best college degrees for the future. These majors are aligned with emerging technologies and industry demands, ensuring long-term career growth and sustainability.
