| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Engineering and Technology | 878 | 22 | 28 | 9 |
IEEE Journal of Translational Engineering in Health and Medicine is mainly concerned with subjects like Artificial intelligence, Pattern recognition, Physical medicine and rehabilitation, Computer vision and Feature extraction. The study on Artificial intelligence presented in it intersects with the topics under Machine learning. The journal holds forums on Physical medicine and rehabilitation that merges themes from other disciplines such as Rehabilitation and Stroke.
In the journal, researchers investigate the Image segmentation study as part of research in the field of Segmentation.
The journal articles focus on Artificial intelligence, Physical medicine and rehabilitation, Feature extraction, Remote patient monitoring and Wearable computer. In addition to Artificial intelligence research, the most cited papers aim to explore topics under Machine learning, Computer vision and Pattern recognition. While work presented in the journal papers provide substantial information on Physical medicine and rehabilitation, it also covers topics in Rehabilitation, Physical therapy and Ankle.
The main points discussed in IEEE Journal of Translational Engineering in Health and Medicine deals with Artificial intelligence, Pattern recognition, Physical medicine and rehabilitation, Computer vision and Electroencephalography. In addition to Artificial intelligence research, IEEE Journal of Translational Engineering in Health and Medicine aims to explore topics under Machine learning and Identification (information). Aside from investigating topics in Convolutional neural network under Pattern recognition, it also explores concepts in Graphical user interface.
The journal tackles studies in Stroke and the interrelated subject of Upper limb and Activities of daily living to gain insights into Physical medicine and rehabilitation. The research on Computer vision tackled can also make contributions to studies in the areas of Robot, Medical robot and Matched filter. In it, Visual analogue scale, Sample entropy, Electromyography and Human brain are investigated in conjunction with one another to address concerns in Electroencephalography 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 IEEE Journal of Translational Engineering in Health and Medicine (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 Journal of Translational Engineering in Health and Medicine (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, 4.26% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 13.33% were posted by at least one author from the top 10 institutions publishing in the journal. Another 8.89% 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 55.56% 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.
Arvind Gautam;Madhuri Panwar;Archana Wankhede;Sridhar P. Arjunan
(2020)Patrick Mcgurrin;James Mcnames;Tianxia Wu;Mark Hallett
(2021)Jeonghee Kim;Thomas Wichmann;Omer T. Inan;Stephen P. Deweerth
(2020)Conor Mackle;Raymond Bond;Hannah Torney;Ronan Mcbride
(2020)Min Jing;Donal McLaughlin;Sara E E McNamee;Shasidran Raj
(2021)Terence Sanger;Anthony Chang;William Feaster;Sharief Taraman
(2021)Yikang Guo;Li Wang;Yan Xiao;Yingzi Lin
(2021)Bekah Allen;Robert Molokie;Thomas J. Royston
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