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Record W2474000235 · doi:10.15265/iys-2016-s003

Visualization of the IMIA Yearbook of Medical Informatics Publications over the Last 25 Years

2016· article· en· W2474000235 on OpenAlex
H. Tam-Tham, Evan Minty, Dean Yergens

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueYearbook of Medical Informatics · 2016
Typearticle
Languageen
FieldHealth Professions
TopicElectronic Health Records Systems
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsYearbookHealth informaticsComputer scienceInformaticsData scienceBibliometricsVisualizationWorld Wide WebLibrary scienceHealth careData miningPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: The last 25 years have been a period of innovation in the area of medical informatics. The International Medical Informatics Association (IMIA) has published, every year for the last quarter century, the Yearbook of Medical Informatics, collating selected papers from various journals in an attempt to provide a summary of the academic medical informatics literature. The objective of this paper is to visualize the evolution of the medical informatics field over the last 25 years according to the frequency of word occurrences in the papers published in the IMIA Yearbook of Medical Informatics. METHODS: A literature review was conducted examining the IMIA Yearbook of Medical Informatics between 1992 and 2015. These references were collated into a reference manager application to examine the literature using keyword searches, word clouds, and topic clustering. The data was considered in its entirety, as well as segregated into 3 time periods to examine the evolution of main trends over time. Several methods were used, including word clouds, cluster maps, and custom developed web-based information dashboards. RESULTS: The literature search resulted in a total of 1210 references published in the Yearbook, of which 213 references were excluded, resulting in 997 references for visualization. Overall, we found that publications were more technical and methods-oriented between 1992 and 1999; more clinically and patient-oriented between 2000 and 2009; and noted the emergence of "big data", decision support, and global health in the past decade between 2010 and 2015. Dashboards were additionally created to show individual reference data, as well as, aggregated information. CONCLUSION: Medical informatics is a vast and expanding area with new methods and technologies being researched, implemented, and evaluated. Determining visualization approaches that enhance our understanding of literature is an active area of research, and like medical informatics, is constantly evolving as new software and algorithms are developed. This paper examined several approaches for visualizing the medical informatics literature to show historical trends, associations, and aggregated summarized information to illustrate the state and changes in the IMIA Yearbook publications over the last quarter century.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.550
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.043
GPT teacher head0.423
Teacher spread0.380 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it