ArticleJournal of digital imaging2015
Strategies for medical data extraction and presentation part 1: current limitations and deficiencies.
Article in Journal of digital imaging, 2015. 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.
- Strategies for Medical Data Extraction and Presentation Part 3: Automated Context- and User-Specific Data Extraction.Journal of digital imaging · 2015Review
- Strategies for medical data extraction and presentation part 2: creating a customizable context and user-specific patient reference database.Journal of digital imaging · 2015Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Data overload is a burgeoning challenge for the medical imaging community; with resulting technical, clinical, and economic ramifications. A primary concern for radiologists is the timely, efficient, and accurate extraction of imaging and clinical data, which collectively are essential in determining accurate diagnosis. In current practice, imaging data retrieval is limited by the fact that imaging and report data are de-coupled from one another, along with the non-standardized and often ambiguous free text data contained within narrative radiology reports. Clinical data retrieval is equally challenging and flawed by the lack of information system integration, paucity of clinical order entry data, and diminished role of the technologist in providing clinical data. These combined factors have the potential to adversely affect radiologist performance and clinical outcomes by diminishing workflow, report accuracy, and diagnostic confidence. New and innovative strategies are required to improve and automate data extraction and presentation, in a context- and user-specific fashion.
Indexed as
Identifiers
What 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.