| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 185 | 126 | 406 | 28 |
| Engineering and Technology | 652 | 34 | 49 | 13 |
The journal tackles a plethora of topics, such as Artificial intelligence, Computer vision, Segmentation, Pattern recognition and Deep learning. In addition to Artificial intelligence research, International Journal of Computer Assisted Radiology and Surgery aims to explore topics under Imaging phantom and Machine learning. Most of the Computer vision studies addressed also intersect with Robot.
The study on Segmentation presented in it intersects with the topics under Radiology.
The published articles primarily tackle Artificial intelligence, Segmentation, Convolutional neural network, Pattern recognition and Computer vision. The journal papers explore topics in Artificial intelligence which can be helpful for research in disciplines like Machine learning and Radiology. While work presented in the most cited publications provide substantial information on Computer vision, it also covers topics in Imaging phantom, Surgical planning and Visualization.
The foci of the journal are Artificial intelligence, Pattern recognition, Deep learning, Segmentation and Computer vision. Artificial intelligence research featured in the journal incorporates concerns from various other topics such as Imaging phantom and Machine learning. The Pattern recognition works featured in the journal incorporate elements from Image (mathematics), Similarity (geometry) and Feature (computer vision).
Topics in Deep learning were tackled in line with various other fields like Network architecture and Radiography. While Segmentation is the focus of it, it also provided insights into the studies of Generalization, Magnetic resonance imaging, Surgical planning and Hausdorff distance. Topics in Computer vision explored in International Journal of Computer Assisted Radiology and Surgery were investigated in conjunction with research in Point (geometry) and Process (computing).
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 International Journal of Computer Assisted Radiology and Surgery (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 International Journal of Computer Assisted Radiology and Surgery (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, 3.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 26.11% were posted by at least one author from the top 10 institutions publishing in the journal. Another 12.83% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 21.68% of all publications and 39.38% 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.
Beyond developing academic research and insights, the field of computer assisted radiology and surgery presents a range of unique career opportunities. Given the rapidly advancing technology and increasing demand for such specialized skills, exploring this professional path can be equally lucrative and satisfying. Those with a strong foundation in computer science, artificial intelligence, and medical imaging can find opportunities in hospitals, medical research centers, academic institutions, and private technology companies. For instance, job roles can range from research scientists focused on AI in medical imaging to software developers creating intuitive tools for radiologists and surgeons. It’s also important to note that educators hold considerable influence in this field. By teaching the next generation of specialists, individuals can contribute to the advancements in this sector while shaping future thought leaders. For instance, a career in teaching elementary art could transform into a specialized role, teaching young minds about the intersection of technology and medical sciences in a simplified, accessible manner. If you're curious about transitioning into academia, this guide on [how to become an elementary art teacher in Nevada](https://research.com/careers/how-to-become-an-art-teacher-in-nevada) serves as a great starting point, with applicable tips to any teaching roles in the tech-medical field. In conclusion, the field of computer assisted radiology and surgery offers a wide array of career paths that contribute significantly to supporting global health infrastructure. It's an excellent time to explore these opportunities and make impactful contributions.
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