| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 211 | 151 | 185 | 25 |
| Medicine | 862 | 250 | 196 | 25 |
BMC Medical Informatics and Decision Making primarily tackles Health informatics, Artificial intelligence, Health care, Nursing and Knowledge management. Topics in Health informatics explored in it were investigated in conjunction with research in Clinical decision support system, Decision support system, Family medicine, Medical education and Medical emergency. The work on Artificial intelligence tackled in BMC Medical Informatics and Decision Making brings together disciplines like Machine learning, Pattern recognition and Natural language processing.
The most cited papers mainly deal with areas of study such as Health informatics, Health care, Nursing, Knowledge management and Artificial intelligence. The Health informatics research presented in the most cited papers focuses mostly on Decision support system and, on occasion, topics in Decision aids. The works on Artificial intelligence tackled in the journal articles bring together disciplines like Machine learning, Data mining and Natural language processing.
BMC Medical Informatics and Decision Making mainly tackles studies in Health informatics, Artificial intelligence, Health care, Machine learning and Clinical decision support system. Test (assessment), Context (language use), Family medicine, Medical education and Medical emergency are some topics wherein Health informatics research discussed in it have an impact. It focuses on Artificial intelligence but the discussions also offer insight into other areas such as Natural language processing and Pattern recognition.
The journal features Health care research that overlaps with concepts in Usability. Decision tree and Receiver operating characteristic are some of the study areas of Machine learning discussed. In addition to Random forest research, it aims to explore topics under Logistic regression and Support vector machine.
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 BMC Medical Informatics and Decision Making (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 BMC Medical Informatics and Decision Making (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, 3.24% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 7.43% were posted by at least one author from the top 10 institutions publishing in the journal. Another 8.92% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 15.24% of all publications and 68.40% 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.
Determining a career path in the fields of medical informatics and decision making, whether it’s in health care or artificial intelligence, requires more than just an understanding of the research topics and academic expertise. It is also essential to grasp the societal and economic implications of these professions. For instance, insights into average salaries, job opportunities, and career growth are paramount. Such vital information provides a realistic picture of what prospective job seekers in these fields can expect, guiding their decisions on whether to pursue related studies and careers. For illustrative purposes, consider the career of a preschool teacher assistant in Wyoming. Candidates seeking such a role would need to know the education or training requirements, job prospects, and, more importantly, the potential earnings. You can access specific info on the [preschool teacher assistant salary in Wyoming](https://research.com/careers/how-to-become-a-preschool-teacher-assistant-in-wyoming) for a comprehensive understanding of the economic implications of this career. The same principles apply to advanced fields in medical informatics, artificial intelligence, and decision making. Prospective professionals need to have a clear grasp of the job market, average salaries, education requirements, and career development opportunities. Therefore, detailed research and information in these areas are vital for those considering a profession in these disciplines.
Davide Chicco;Giuseppe Jurman
(2020)James E. Harrison;Stefanie Weber;Robert Jakob;Christopher G. Chute
(2021)Salem T. Argaw;Juan Ramón Troncoso-Pastoriza;Darren Lacey;Marie-Valentine Florin
(2020)Li Tong;Jonathan Mitchel;Kevin Chatlin;May D. Wang
(2020)André M. Carrington;Paul W. Fieguth;Hammad Qazi;Andreas Holzinger;Andreas Holzinger
(2020)Yan-Bin Wang;Zhu-Hong You;Shan Yang;Hai-Cheng Yi
(2020)Fazle Rabby;Yazhou Tu;Imran Hossen;Insup Lee
(2021)Sarah Charlotte Johnson;Matthew Cunningham;Ilse N. Dippenaar;Fablina Sharara
(2021)For students interested in Medicine in the USA, exploring related online degrees can broaden career opportunities. Fields like medical coding and health information management are crucial to healthcare and often require less time to complete compared to a traditional medical degree. For those wondering how long does it take to become a medical coder, many programs offer certificates or associate degrees that can be completed in under two years.
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