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Journal of Biomedical and Health Informatics
H-index 78

Journal of Biomedical and Health Informatics

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Computer Science 32 664 1076 72
Engineering and Technology 155 93 185 36

Additional Metrics

Number of Best Scientists*: 1102
Documents by Best Scientists*: 1426
Top 100 Ranked Scientists*: 26
SCIMAGO H-index: 168
SCIMAGO SJR: 1.649
Impact Factor: 6.8

Overview

Top Research Topics at IEEE Journal of Biomedical and Health Informatics?

The journal primarily tackles Artificial intelligence, Pattern recognition, Feature extraction, Deep learning and Machine learning. The study on Artificial intelligence presented in the journal intersects with subjects under the field of Computer vision. The Computer vision research dealing mostly with Image processing is the focus of it.

In addition to Pattern recognition research, it aims to explore topics under Speech recognition, Signal processing, Feature (computer vision) and Electroencephalography. The study on Machine learning presented is investigated in conjunction with research in Data modeling.

  • Artificial intelligence (51.80%)
  • Pattern recognition (28.11%)
  • Feature extraction (16.92%)

What are the most cited papers published in the journal?

  • A Survey on Ambient-Assisted Living Tools for Older Adults (736 citations)
  • Deep EHR: A Survey of Recent Advances in Deep Learning Techniques for Electronic Health Record (EHR) Analysis (458 citations)
  • Big Data for Health (380 citations)

Research areas of the most cited articles at IEEE Journal of Biomedical and Health Informatics:

The journal papers investigate studies in Artificial intelligence, Pattern recognition, Feature extraction, Computer vision and Support vector machine. Most of the works presented in the most cited publications deal with Artificial intelligence but they intersect with the subject of Machine learning. The published articles deal with Pattern recognition in conjunction with Electroencephalography and similar fields in Epilepsy.

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

  • Artificial intelligence
  • Internal medicine
  • Statistics

The previous edition focused in particular on these issues:

The journal primarily focuses on research topics in Artificial intelligence, Pattern recognition, Deep learning, Feature extraction and Machine learning. Artificial intelligence, which encompasses Segmentation, Convolutional neural network, Image segmentation, Artificial neural network and Feature (computer vision), is the main subject of IEEE Journal of Biomedical and Health Informatics. While Pattern recognition is the focus of IEEE Journal of Biomedical and Health Informatics, it also provided insights into the studies of Robustness (computer science) and Electroencephalography.

The journal features Deep learning research that overlaps with concepts in Transfer of learning. It explores issues in Machine learning which can be linked to other research areas like Data modeling and Task analysis.

The most cited articles from the last journal are:

  • Multi-Scale Self-Guided Attention for Medical Image Segmentation (96 citations)
  • COVID-19 CT Image Synthesis With a Conditional Generative Adversarial Network (28 citations)
  • An Efficient Ciphertext-Policy Weighted Attribute-Based Encryption for the Internet of Health Things (24 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.

The top authors publishing in IEEE Journal of Biomedical and Health Informatics (based on the number of publications) are:

  • Omer T. Inan (20 papers) published 7 papers at the last edition, 1 more than at the previous edition,
  • Yuan-Ting Zhang (19 papers) published 6 papers at the last edition, 1 more than at the previous edition,
  • Dinggang Shen (16 papers) published 3 papers at the last edition, 2 less than at the previous edition,
  • David A. Clifton (15 papers) published 5 papers at the last edition, 1 more than at the previous edition,
  • Benny Lo (15 papers) published 3 papers at the last edition, 1 less than at the previous 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.

Only papers with recognized affiliations are considered

The top affiliations publishing in IEEE Journal of Biomedical and Health Informatics (based on the number of publications) are:

  • Shanghai Jiao Tong University (45 papers) published 18 papers at the last edition, 15 more than at the previous edition,
  • Chinese Academy of Sciences (45 papers) published 17 papers at the last edition, 7 more than at the previous edition,
  • Imperial College London (44 papers) published 7 papers at the last edition, 4 less than at the previous edition,
  • The Chinese University of Hong Kong (41 papers) published 9 papers at the last edition, 2 more than at the previous edition,
  • Georgia Institute of Technology (35 papers) published 10 papers at the last edition, 1 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, 15.34% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 19.14% were posted by at least one author from the top 10 institutions publishing in the journal. Another 9.37% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 17.72% of all publications and 53.77% 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.

Career Opportunities in Biomedical and Health Informatics

While this article provides detailed insight into the research topics, most cited papers, and the affiliations analysis of the IEEE Journal of Biomedical and Health Informatics, it is also equally important to look at the potential career pathways that a focus in Biomedical and Health Informatics may have. As the field expands, skilled professionals are increasingly in demand in various sectors including academia, industry, healthcare, and government agencies.

Career options range from clinical informatics specialists, health information managers, health data analysts to informatics consultants, and researchers. Depending on your professional interests, you may also consider becoming a teacher in related fields. For example, if you are interested in shaping future generations and reside in Maryland, you might want to check out this guide on {anchor}.

The career opportunities within the realm of Biomedical and Health Informatics extend far beyond these roles, with many organizations recognizing the importance of this expertise. Therefore, it is advised to continually seek knowledge and stay updated on the cutting-edge research topics, as presented in scientific journals like the IEEE Journal of Biomedical and Health Informatics.

Top Publications

  • AI in Medical Imaging Informatics: Current Challenges and Future Directions

    Andreas S. Panayides;Amir Amini;Nenad D. Filipovic;Ashish Sharma

    (2020)
    581 Citations
  • COVIDGR Dataset and COVID-SDNet Methodology for Predicting COVID-19 Based on Chest X-Ray Images

    S. Tabik;A. Gomez-Rios;J. L. Martin-Rodriguez;I. Sevillano-Garcia

    (2020)
    361 Citations
  • Convolutional Recurrent Neural Networks for Glucose Prediction

    Kezhi Li;John Daniels;Chengyuan Liu;Pau Herrero

    (2020)
    307 Citations
  • A Comprehensive Study on Colorectal Polyp Segmentation With ResUNet++, Conditional Random Field and Test-Time Augmentation

    Debesh Jha;Pia H. Smedsrud;Dag Johansen;Thomas de Lange

    (2021)
    303 Citations
  • Epilepsy Seizure Prediction on EEG Using Common Spatial Pattern and Convolutional Neural Network

    Yuan Zhang;Yao Guo;Po Yang;Wei Chen

    (2020)
    283 Citations
  • Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XL

    Nils Strodthoff;Patrick Wagner;Tobias Schaeffter;Wojciech Samek

    (2021)
    267 Citations
  • Unsupervised 3D End-to-End Medical Image Registration With Volume Tweening Network

    Shengyu Zhao;Tingfung Lau;Ji Luo;Eric I-Chao Chang

    (2020)
    254 Citations
  • Decentralized Authentication of Distributed Patients in Hospital Networks Using Blockchain

    Abbas Yazdinejad;Gautam Srivastava;Reza M. Parizi;Ali Dehghantanha

    (2020)
    247 Citations
  • A Patient-Centric Health Information Exchange Framework Using Blockchain Technology

    Yan Zhuang;Lincoln R. Sheets;Yin-Wu Chen;Zon-Yin Shae

    (2020)
    231 Citations
  • Adaptive Feature Selection Guided Deep Forest for COVID-19 Classification With Chest CT

    Liang Sun;Zhanhao Mo;Fuhua Yan;Liming Xia

    (2020)
    220 Citations

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Best Scientists Contributing to This Journal

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