| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 85 | 268 | 404 | 46 |
| Engineering and Technology | 162 | 199 | 394 | 35 |
The journal investigates studies in Artificial intelligence, Biomedical engineering, Computer vision, Pattern recognition and Electronic engineering. IEEE Transactions on Biomedical Engineering explores topics in Artificial intelligence which can be helpful for research in disciplines like Machine learning, Speech recognition, Electroencephalography and Signal processing. The study on Signal processing presented is investigated in conjunction with research in Algorithm.
The studies on Biomedical engineering discussed can also contribute to research in the domains of Electrode and Ultrasound. The journal encompasses presentations on Computer vision, specifically Image processing, Image segmentation and Segmentation. The Electronic engineering study tackled is a key component of adjacent topics in the area of Acoustics.
The published papers are organized to address concerns in the fields of Artificial intelligence, Biomedical engineering, Pattern recognition, Speech recognition and Signal processing. The studies on Artificial intelligence discussed at the journal publications can also contribute to research in the domains of Machine learning and Computer vision. The journal publications explore issues in Signal processing which can be linked to other research areas like Algorithm and Electronic engineering.
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 IEEE Transactions on Biomedical Engineering (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 IEEE Transactions on Biomedical Engineering (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, 18.95% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 11.33% were posted by at least one author from the top 10 institutions publishing in the journal. Another 10.60% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 18.80% of all publications and 59.28% 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 the fields of Artificial intelligence, Biomedical engineering, Computer vision, Pattern recognition, and Electronic engineering provide rewarding pathways in research, it is important to mention that these areas of specialization can also lead to fulfilling careers in the education sector. Virginia, for example, has a high demand for private school teachers specializing in these STEM areas.
Oftentimes, academics who thrive in research environments also excel at conveying complex concepts to students, enabling the next generation of innovators to develop a solid understanding of these rapidly evolving sectors. To explore this alternative career path, academic professionals may want to consider becoming private school teachers in states with a strong focus on STEM education.
While specific requirements may vary from state to state, generally a bachelor's degree in the field of study you plan to teach is required. Prospective teachers are usually also expected to complete a teacher training program. However, in some states like Virginia, private schools can set their own requirements for teacher qualifications.
For example, to help guide you through the process of becoming a private school teacher in Virginia, this article on do private school teachers need a degree in Virginia provides a comprehensive overview of the necessary steps to embark on this rewarding career. Utilizing the skills and knowledge accumulated during research work in the classroom can be a beneficial path for those wishing to directly influence the next generation of researchers and engineers.
Hao Guan;Mingxia Liu
(2021)Chi-Yuan Chang;Sheng-Hsiou Hsu;Luca Pion-Tonachini;Tzyy-Ping Jung
(2020)He He;Dongrui Wu
(2020)Changhee Lee;Jinsung Yoon;Mihaela van der Schaar
(2020)Ruyi Foong;Ning Tang;Effie Chew;Karen Sui Geok Chua
(2020)Huy Phan;Oliver Y. Chen;Philipp Koch;Zongqing Lu
(2021)Coen de Vente;Pieter Vos;Matin Hosseinzadeh;Josien Pluim
(2021)For students interested in pursuing Computer Science, exploring related online degrees can open diverse career pathways. While Computer Science itself is known as one of the most profitable degrees, other tech-focused programs like data science or information systems also offer strong earning potential and growth.
Cost is a significant factor for many learners seeking online education. Fortunately, there are numerous cheap online colleges that provide quality Computer Science programs without burdening students with excessive debt.
Admissions processes can be streamlined as well, with some institutions listed among the best online colleges with no application fee. This allows prospective students to apply effortlessly and explore various options before making a commitment.
Additionally, many universities offer fast-paced options ideal for those eager to enter the workforce quickly. Accelerated programs featured in fast track school programs enable students to earn their degree in reduced timeframes, balancing education with career demands.
