Tampere , Finland
Conference Dates: Sep 04, 2022 - Sep 07, 2022
The conference covers a variety of subjects, including Internal medicine, Cardiology, Electrocardiography, Artificial intelligence and Pattern recognition. Discussions in the conference are anchored in the subject of Internal medicine and the similar topic of Anesthesia. The presented Cardiology study covers related areas such as Hemodynamics, Myocardial infarction and Heart failure and also touches on topics like In patient.
In addition to Electrocardiography research, Computing in Cardiology Conference aims to explore topics under Remote patient monitoring, QRS complex, Ventricular tachycardia and QT interval. The conference explores topics in Artificial intelligence which can be helpful for research in disciplines like Machine learning, Speech recognition and Computer vision. The event is mostly focused on Computer vision, specifically Image segmentation.
Computing in Cardiology Conference tackles topics on Image segmentation, which can potentially contribute to the wider field of Segmentation. The Pattern recognition study featured in Computing in Cardiology Conference draws connections with the study of Signal. Studies on Heart rate variability discussed in it link to the field of Autonomic nervous system.
The conference papers mostly deal with topics like Artificial intelligence, Electrocardiography, Internal medicine, Cardiology and Pattern recognition. The studies on Artificial intelligence discussed at the conference papers can also contribute to research in the domains of Machine learning, Speech recognition and Computer vision. The most cited articles facilitate discussions on Electrocardiography that incorporate concepts from other fields like QRS complex, Heart rate variability, Heart rate, Atrial fibrillation and Algorithm.
The topics of Artificial intelligence, Pattern recognition, Internal medicine, Cardiology and Atrial fibrillation are the focal point of discussions in Computing in Cardiology Conference. Some problems in Artificial intelligence that were presented in Computing in Cardiology Conference overlapped with concepts under Test score and Machine learning. While work presented in the event provided substantial information on Pattern recognition, it also covered topics in Ranking, QRS complex and Test set.
Electrocardiography, Sinus rhythm, Heart rate variability, Heart rate and Healthy subjects are all aspects of Internal medicine research featured in Computing in Cardiology Conference. Electrocardiography research presented in the event encompasses a variety of subjects, including Feature (computer vision) and Catheter ablation. The conference connects the study in Cardiology with the closely related area of Lead (electronics).
A key indicator for each conference 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 at Computing in Cardiology Conference (based on the number of publications) are:
The overall trend for top authors publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing at Computing in Cardiology Conference (based on the number of publications) are:
The overall trend for top affiliations publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions at the conference edition to all articles published within that conference. The best research institutions were selected based on the largest number of articles published during all editions of the conference.
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 2020 edition, 5.70% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 31.67% were posted by at least one author from the top 10 institutions publishing at the conference. Another 16.01% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 18.15% of all publications and 34.16% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of conferences they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same conference 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 conference 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 at a conference. The index includes the authors publishing at the last edition of a conference, 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.
Computing in Cardiology Conference
Thank you for information!