ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2019
Assessing the Readability of Freely Available ICU Notes.
Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- DI++: A deep learning system for patient condition identification in clinical notes.Artificial intelligence in medicine · 2022Article
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
No grant is acknowledged in the PubMed record.
Abstract
Unstructured data stored in an electronic health record (EHR) system can be very informative but require techniques such as natural language processing to extract the information. Developing such techniques requires shared data, but clinical data are often not easy to access. A freely available intensive care unit database, MIMIC-III, was released in 2016 to address this issue and benefit the informatics research community. While the database has been utilized by a few studies, the text characteristics of the notes have not been summarized. In this study, we present the summary of the basic text characteristics and the readability of the MIMIC-III ICU notes. We further compare the results with our previous study where proprietary EHR notes were used. The results show that the text
Identifiers
31259026PMC6568110What 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.