Journal of Healthcare Engineering

Top Research Topics at Journal of Healthcare Engineering?

The primary areas of discussion in Journal of Healthcare Engineering are Artificial intelligence, Pattern recognition, Health care, Machine learning and MEDLINE. Artificial intelligence research discussed connects with the study of Computer vision. It emphasizes research on Segmentation, which includes concerns such as Image segmentation.

• Artificial intelligence (26.42%)
• Pattern recognition (10.43%)
• Health care (7.14%)

What are the most cited papers published in the journal?

• Using Deep Learning for Classification of Lung Nodules on Computed Tomography Images. (140 citations)
• Locomotor training in subjects with sensori-motor deficits: An overview of the robotic gait orthosis lokomat (139 citations)
• An Efficient Deep Learning Approach to Pneumonia Classification in Healthcare. (137 citations)

Research areas of the most cited articles at Journal of Healthcare Engineering:

The journal articles mainly deal with areas of study such as Artificial intelligence, Artificial neural network, Pattern recognition, Machine learning and Deep learning. The published articles with studies in Artificial intelligence featured incorporate elements of Computer vision and Signal processing. The journal publications focus on Pattern recognition but the discussions also offer insight into other areas such as Photoplethysmogram and Magnetic resonance imaging.

What topics the last edition of the journal is best known for?

• Internal medicine
• Surgery
• Artificial intelligence

The previous edition focused in particular on these issues:

Journal of Healthcare Engineering covers a variety of subjects, including Artificial intelligence, Pattern recognition, Deep learning, Machine learning and Internal medicine. Segmentation, Convolutional neural network, Artificial neural network, Support vector machine and Feature (computer vision) are all topics related to Artificial intelligence research discussed. Image segmentation is part of Segmentation studies tackled in it.

It features studies on Machine learning, including topics such as Random forest. While it focused on Internal medicine, it was also able to explore topics like Gastroenterology and Cardiology.

The most cited articles from the last journal are:

• Metaheuristic-based Deep COVID-19 Screening Model from Chest X-Ray Images. (14 citations)
• Deep Learning in the Detection and Diagnosis of COVID-19 Using Radiology Modalities: A Systematic Review. (13 citations)
• AGTH-Net: Attention-Based Graph Convolution-Guided Third-Order Hourglass Network for Sports Video Classification. (12 citations)

Papers citation over time

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.

Top authors and change over time

The top authors publishing in Journal of Healthcare Engineering (based on the number of publications) are:

• Yubo Fan (10 papers) published 2 papers at the last edition, 1 more than at the previous edition,
• Bing Zhou (9 papers) published 5 papers at the last edition, 4 more than at the previous edition,
• Zongmin Wang (9 papers) published 4 papers at the last edition, 3 more than at the previous edition,
• M. Irfan Uddin (7 papers) published 3 papers at the last edition, 1 less than at the previous edition,
• Linhong Ji (6 papers) absent at the last edition.

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.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing in Journal of Healthcare Engineering (based on the number of publications) are:

• Zhengzhou University (28 papers) published 11 papers at the last edition, 8 more than at the previous edition,
• Zhejiang University (23 papers) published 14 papers at the last edition, 12 more than at the previous edition,
• Shandong University (19 papers) published 11 papers at the last edition, 9 more than at the previous edition,
• Beihang University (19 papers) published 2 papers at the last edition the same number as at the previous edition,
• Sichuan University (19 papers) published 9 papers at the last edition, 8 more than at the previous edition.

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.

Publication chance based on affiliation

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, 20.96% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 19.13% were posted by at least one author from the top 10 institutions publishing in the journal. Another 8.70% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 17.83% of all publications and 54.35% were from other institutions.

Returning Authors Index

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.

Returning Institution Index

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.

The experience to innovation index

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:

• Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
• Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
• Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
• Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
• Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.