Journal of Biomedical Informatics

Top Research Topics at Journal of Biomedical Informatics?

Journal of Biomedical Informatics focuses on Artificial intelligence, Data mining, Natural language processing, Machine learning and Information retrieval. The studies tackled, which mainly focus on Artificial intelligence, apply to Pattern recognition as well. More specifically, the research on Natural language processing in Journal of Biomedical Informatics is related to Unified Medical Language System.

The main emphasis of Journal of Biomedical Informatics is the subject of Information retrieval, focusing on Ontology (information science).

• Artificial intelligence (28.84%)
• Data mining (13.67%)
• Natural language processing (13.37%)

What are the most cited papers published in the journal?

• Research electronic data capture (REDCap)-A metadata-driven methodology and workflow process for providing translational research informatics support (18186 citations)
• The REDCap consortium: Building an international community of software platform partners. (2823 citations)
• miRWalk - Database: Prediction of possible miRNA binding sites by walking the genes of three genomes (1302 citations)

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

The journal articles facilitate discussions on Artificial intelligence, Natural language processing, Data science, Knowledge management and Data mining. Machine learning, Information retrieval and Pattern recognition are some topics wherein Artificial intelligence research discussed in the published papers has an impact. In addition to Data science research, the most cited publications aim to explore topics under MEDLINE, Field (computer science), Terminology, Health informatics and Process (engineering).

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

• Artificial intelligence
• Statistics
• Internal medicine

The previous edition focused in particular on these issues:

Artificial intelligence, Machine learning, Natural language processing, Context (language use) and Deep learning are among the topics commonly tackled in the journal. The journal explores issues in Artificial intelligence which can be linked to other research areas like Pattern recognition, Task (project management) and Identification (information). Topics in Machine learning were tackled in line with various other fields like Relationship extraction, Medical diagnosis and Process (engineering).

Natural language processing research is the primary subject tackled in Journal of Biomedical Informatics with a focus on Information extraction. The Deep learning study tackled is a key component of adjacent topics in the area of Recurrent neural network.

The most cited articles from the last journal are:

• The role of explainability in creating trustworthy artificial intelligence for health care: A comprehensive survey of the terminology, design choices, and evaluation strategies. (18 citations)
• A review on deep learning approaches in healthcare systems: Taxonomies, challenges, and open issues. (16 citations)
• Drug repurposing for COVID-19 via knowledge graph completion. (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 Biomedical Informatics (based on the number of publications) are:

• Vimla L. Patel (42 papers) absent at the last edition,
• George Hripcsak (40 papers) published 1 paper at the last edition, 1 less than at the previous edition,
• Chunhua Weng (38 papers) published 5 papers at the last edition, 3 more than at the previous edition,
• James J. Cimino (30 papers) absent at the last edition,
• Yehoshua Perl (28 papers) published 1 paper at the last edition the same number as 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.

Top affiliations and change over time

Only papers with recognized affiliations are considered

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

• Columbia University (182 papers) published 8 papers at the last edition, 2 more than at the previous edition,
• University of Utah (91 papers) published 6 papers at the last edition, 2 more than at the previous edition,
• Stanford University (79 papers) published 10 papers at the last edition, 8 more than at the previous edition,
• University of Washington (76 papers) published 6 papers at the last edition, 3 more than at the previous edition,
• National Institutes of Health (73 papers) published 4 papers at the last edition, 3 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, 11.07% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 19.11% were posted by at least one author from the top 10 institutions publishing in the journal. Another 8.44% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 12.44% of all publications and 60.00% 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 trajectories in Biomedical Informatics

For anyone interested in contributing to the Journal of Biomedical Informatics or simply joining the fascinating world of Biomedical Informatics, it is important to understand potential career paths and steps to success in this field. Any aspiring professionals could benefit by starting from a role in a related field, such as education. For instance, you could begin your career as a preshool teacher, which can lay down the basis for communicating complex concepts, a valuable skill in any scientific domain. Being from Virginia, you may want to check out how to become a preschool teacher in Virginia as your first step. It's never too early to start building those foundational skills in education and communication. After gaining experience in the field of education, you may then transition to biomedical informatics and contribute to journals such as the Journal of Biomedical Informatics. An academic career in Biomedical Informatics often follows a path through bachelor’s and master’s degrees, PhD programs, postdoctoral research, and often eventually lands you university faculty positions. However, every journey is as unique as the individual who embarks upon it, and yours might be different. Remember, countless possibilities lie ahead in the field of Biomedical Informatics. Whether you strive to be an author in the Journal of Biomedical Informatics, desire to raise the next generation of researchers, or aspire to lead your own informatics research team, starting your journey with a solid foundation and a strategic career pathway can lead you to your destination.