ArticleStudies in health technology and informatics2018
Biomedical Informatics Investigator.
Article in Studies in health technology and informatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Rosacea Patients Are at Higher Risk for Obstructive Sleep Apnea: Automated Retrospective Research.Studies in health technology and informatics · 2020Article
- Sustainable Health Informatics: Health Informaticians as Alchemists.Studies in health technology and informatics · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
The BMI Investigator is a computer human interface built in .Net which allows simultaneous query of structured data such as demographics, administrative codes, medications (coded in RxNorm), laboratory test results (coded in LOINC) and formerly unstructured data in clinical notes (coded in SNOMED CT). The ontology terms identified using SNOMED are all coded as either positive, negative or uncertain assertions. They are then where applicable built into compositional expressions and stored in both a graph database and a triple store. The SNOMED CT codes are stored in a NOSQL database, Berkley DB, and the structured data is stored in SQL using the OMOP/OHDSI format. The BMI investigator also lets you develop models for cohort selection (data driven recruitment to clinical trials) and automated retrospective research using genomic criteria and we are adding image feature data currently to the system. We performed a usability experiment and the users identified some usability flaws which were used to improve the software. Overall, the BMI Investigator was felt to be usable by subject matter experts. Next steps for the software are to integrate genomic criteria and image features into the query engine.
Indexed as
Identifiers
30306935PMC7847179What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.