ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2017
Bar charts detection and analysis in biomedical literature of PubMed Central.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Article
- A systematic review and meta-analysis on the correlation between HIV infection and multidrug-resistance tuberculosis.Heliyon · 2023Article
- A Real-World Approach on the Problem of Chart Recognition Using Classification, Detection and Perspective Correction.Sensors (Basel, Switzerland) · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Bar charts are crucial to summarize and present multi-faceted data sets in biomedical publications. Quantitative information carried by bar charts is of great interest to scientists and practitioners, which make it valuable to parse bar charts. This fact together with the abundance of bar chart images and their shared common patterns gives us a good candidates for automated image mining and parsing. We demonstrate a workflow to analyze bar charts and give a few feasible solutions to apply it. We are able to detect bar segments and panels with a promising performance in terms of both accuracy and recall, and we also perform extensive experiments to identify the entities of bar charts in the images of biomedical literature collected from PubMed Central. While we cannot provide a complete instance of the application using our method, we present evidence that this kind of image mining is feasible.
Indexed as
Identifiers
29854152PMC5977659What 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.