Evidence map›Paper›PMID 28721401›Full record

Article... IEEE-EMBS International Conference on Biomedical and Health Informatics. IEEE-EMBS International Conference on Biomedical and Health Informatics2016

Toward patient-tailored summarization of lung cancer literature.

Jean I Garcia-Gathright, Nicholas J Matiasz, Edward B Garon, Denise R Aberle, Ricky K Taira, Alex A T Bui

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in ... IEEE-EMBS International Conference on Biomedical and Health Informatics. IEEE-EMBS International Conference on Biomedical and Health Informatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Jean I Garcia-GathrightUniversity of California Los Angeles, Department of Bioengineering.
Nicholas J MatiaszUniversity of California Los Angeles, Department of Bioengineering.
Edward B GaronUniversity of California Los Angeles, Department of Medicine.
Denise R AberleUniversity of California Los Angeles, Department of Bioengineering.
Ricky K TairaUniversity of California Los Angeles, Department of Bioengineering.
Alex A T BuiUniversity of California Los Angeles, Department of Bioengineering.

Funding

Training Program for Imaging Based Medical InformaticsT15LM007356 · NLM · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI BUI, ALEX · 2002 to 2011
$5.0M
Medical Imaging Informatics Training GrantT32EB016640 · NIBIB · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ALEX BUI, William Hsu · 2013 to 2026
$2.3M
Data Structuring and Visualization System for Neuro-oncologyR01LM009961 · NLM · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI TAIRA, RICKY K. · 2009 to 2010
$1.7M
NIBIB NIH HHS T32 EB016640NLM NIH HHS R01 LM009961NLM NIH HHS T15 LM007356
6 · The paper itself

Abstract

As the volume of biomedical literature increases, it can be challenging for clinicians to stay up-to-date. Graphical summarization systems help by condensing knowledge into networks of entities and relations. However, existing systems present relations out of context, ignoring key details such as study population. To better support precision medicine, summarization systems should include such information to contextualize and tailor results to individual patients. This paper introduces "contextualized semantic maps" for patient-tailored graphical summarization of published literature. These efforts are demonstrated in the domain of driver mutations in non-small cell lung cancer (NSCLC). A representation for relations and study population context in NSCLC was developed. An annotated gold standard for this representation was created from a set of 135 abstracts; F1-score annotator agreement was 0.78 for context and 0.68 for relations. Visualizing the contextualized relations demonstrated that context facilitates the discovery of key findings that are relevant to patient-oriented queries.

Identifiers

PMID28721401
PMCPMC5511748

What OpenQuestion holds

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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.