Modeling in biomedical informatics—An exploratory analysis

On determining factors for good research in biomedical and health informatics. Some lessons learned

OBJECTIVE

What are the determining factors for good research in medical informatics or, from a broader perspective, in biomedical and health informatics?

METHOD

From the many lessons learned during my professional career, I tried to identify a fair sampling of such factors. On the occasion of giving the IMIA Award of Excellence lecture during MedInfo 2013, they were presented for discussion.

RESULTS

Sixteen determining factors (df) have been identified: early identification and promotion (df1), appropriate education (df2), stimulating persons and environments (df3), sufficient time and backtracking opportunities (df4), breadth of medical informatics competencies (df5), considering the necessary preconditions for good medical informatics research (df6), easy access to high-quality knowledge (df7), sufficient scientific career opportunities (df8), appropriate conditions for sustainable research (df9), ability to communicate and to solve problems (df10), as well as to convey research results (df11) in a highly inter- and multidisciplinary environment, ability to think for all and, when needed, taking the lead (df12), always staying unbiased (df13), always keeping doubt (df14), but also always trying to provide solutions (df15), and, finally, being aware that life is more (df16).

CONCLUSIONS

Medical Informatics is an inter- and multidisciplinary discipline "avant la lettre". Compared to monodisciplinary research, inter- and multidisciplinary research does not only provide significant opportunities for solving major problems in science and in society. It also faces considerable additional challenges for medical informatics as a scientific field. The determining factors, presented here, are in my opinion crucial for conducting successful research and for developing a research career. Since medical informatics as a field has today become an important driving force for research progress, especially in biomedicine and health care, but also in fields like computer science, it may be helpful to consider such factors in relation with research and education in our discipline.

Biomedical informatics publications: a global perspective. Part II: Journals

BACKGROUND

Biomedical Informatics (BMI) is a broad discipline, having evolved from both Medical Informatics (MI) and Bioinformatics (BI). An analysis of publications in the fieldshould provide an indication about the geographic distribution of BMI research contributions and possible lessons for the future, both for research and professional practice.

OBJECTIVES

In part I of our analysis of biomedical informatics publications we presented results from BMI conferences. In this second part, we analyse BMI journals, which provide a broader perspective and comparison between data from conferences and journals that ought to confirm or suggest alternatives to the original distributional findings from the conferences.

METHODS

We manually collected data about authors and their geographical origin from various MI journals: the International Journal of Medical Informatics (IJMI), the Journal of Biomedical Informatics (JBI), Methods of In formation in Medicine (MIM) and The Journal of the American Medical Informatics Association (JAMIA). Focusing on first authors, we also compared these findings with data from the journal Bioinformatics.

RESULTS

Our results confirm those obtained in our analysis of BMI conferences - that local and regional authors favor their corresponding MI journals just as they do their conferences. Consideration of other factors, such as the increasingly open source nature of data and software tools, is consistent with these findings.

CONCLUSIONS

Our analysis suggests various indicators that could lead to further, deeper analyses, and could provide additional insights for future BMI research and professional activities.

Biomedical informatics publications: a global perspective: part I: conferences

BACKGROUND

In the past decade, Medical Informatics (MI) and Bioinformatics (BI) have converged towards a new discipline, called Biomedical Informatics (BMI) bridging informatics methods across the spectrum from genomic research to personalized medicine and global healthcare. This convergence still raises challenging research questions which are being addressed by researchers internationally, which in turn raises the question of how biomedical informatics publications reflect the contributions from around the world in documenting the research.

OBJECTIVES

To analyse the worldwide participation of biomedical informatics researchers from professional groups and societies in the best-known scientific conferences in the field. The analysis is focused on their geographical affiliation, but also includes other features, such as the impact and recognition of the conferences.

METHODS

We manually collected data about authors of papers presented at three major MI conferences: Medinfo, MIE and the AMIA symposium. In addition, we collected data from a BI conference, ISMB, as a comparison. Finally, we analyzed the impact and recognition of these conferences within their scientific contexts.

RESULTS

Data indicate a predominance of local authors at the regional conferences (AMIA and MIE), whereas other conferences with a world-wide scope (Medinfo and ISMB) had broader participation. Our analysis shows that the influence of these conferences beyond the discipline remains somewhat limited.

CONCLUSIONS

Our results suggest that for BMI to be recognized as a broad discipline, both in the geographical and scientific sense, it will need to extend the scope of collaborations and their interdisciplinary impacts worldwide.

Knowledge structure of korean medical informatics: a social network analysis of articles in journal and proceedings

Objectives

This study aimed at exploring the knowledge structure of Korean medical informatics.

Methods

We utilized the keywords, as the main variables, of the research papers that were presented in the journal and symposia of the Korean Society of Medical Informatics, and we used, as cases, the English titles and abstracts of the papers (n = 915) published from 1995 through 2008. N-grams (bigram to 5-gram) were extracted from the corpora using the BiKE Text Analyzer, and their cooccurrence networks were generated via a cosine correlation coefficient, and then the networks were analyzed and visualized using Pajek.

Results

With the hub and authority measures, the most important research topics in Korean medical informatics were identified. Newly emerging topics by three-year period units were observed as research trends.

Conclusions

This study provides a systematic overview on the knowledge structure of Korean medical informatics.