Evidence map›Paper›PMID 29888051›Full record

ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2018

From Sour Grapes to Low-Hanging Fruit: A Case Study Demonstrating a Practical Strategy for Natural Language Processing Portability.

Stephen B Johnson, Prakash Adekkanattu, Thomas R Campion, James Flory, Jyotishman Pathak, Olga V Patterson, Scott L DuVall, Vincent Major, Yindalon Aphinyanaphongs

Abstract read
In one paragraph

Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Stephen B JohnsonHealthcare Policy and Research, Weill Cornell Medicine, New York, New York.
Prakash AdekkanattuInformation Technologies & Services, Weill Cornell Medicine, New York, New York.
Thomas R CampionHealthcare Policy and Research, Weill Cornell Medicine, New York, New York.
James FloryHealthcare Policy and Research, Weill Cornell Medicine, New York, New York.
Jyotishman PathakHealthcare Policy and Research, Weill Cornell Medicine, New York, New York.
Olga V PattersonVA Salt Lake City Health Care System.
Scott L DuVallVA Salt Lake City Health Care System.
Vincent MajorCenter for Health Informatics and Bioinformatics, NYU Langone Medical Center, New York, New York.
Yindalon AphinyanaphongsCenter for Health Informatics and Bioinformatics, NYU Langone Medical Center, New York, New York.

Funding

Improving Metformin Utilization And Diabetes Control Through Patient-Centered Outcomes ResearchK08HS023898 · AHRQ · WEILL MEDICAL COLL OF CORNELL UNIV · PI FLORY, JAMES H · 2015 to 2019
$760k
AHRQ HHS K08 HS023898
6 · The paper itself

Abstract

Natural Language Processing (NLP) holds potential for patient care and clinical research, but a gap exists between promise and reality. While some studies have demonstrated portability of NLP systems across multiple sites, challenges remain. Strategies to mitigate these challenges can strive for complex NLP problems using advanced methods (hard-to-reach fruit), or focus on simple NLP problems using practical methods (low-hanging fruit). This paper investigates a practical strategy for NLP portability using extraction of left ventricular ejection fraction (LVEF) as a use case. We used a tool developed at the Department of Veterans Affair (VA) to extract the LVEF values from free-text echocardiograms in the MIMIC-III database. The approach showed an accuracy of 98.4%, sensitivity of 99.4%, a positive predictive value of 98.7%, and F-score of 99.0%. This experience, in which a simple NLP solution proved highly portable with excellent performance, illustrates the point that simple NLP applications may be easier to disseminate and adapt, and in the short term may prove more useful, than complex applications.

Identifiers

PMID29888051
PMCPMC5961788

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.