Evidence map›Paper›PMID 29149658›Full record

ArticleComputers in biology and medicine2018

Evaluating Casama: Contextualized semantic maps for summarization of lung cancer studies.

Jean I Garcia-Gathright, Nicholas J Matiasz, Carlos Adame, Karthik V Sarma, Lauren Sauer, Nova F Smedley, Marshall L Spiegel, Jennifer Strunck, Edward B Garon, Ricky K Taira and 2 more

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Computers in biology and medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.1field-weighted citation impact, top 48% of its field
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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

12 authors at 1 institution in 1 country.

Jean I Garcia-GathrightUniversity of California, Los Angeles, Department of Bioengineering, 924 Westwood Boulevard, Suite 420, Los Angeles, CA, 90024, USA. Electronic address: jigarcia@ucla.edu.
Nicholas J MatiaszUniversity of California, Los Angeles, Department of Bioengineering, 924 Westwood Boulevard, Suite 420, Los Angeles, CA, 90024, USA.
Carlos AdameUniversity of California, Los Angeles, Department of Medicine - Division of Hematology-Oncology, 924 Westwood Boulevard, Suite 200, Los Angeles, CA, 90024, USA.
Karthik V SarmaUniversity of California, Los Angeles, Department of Bioengineering, 924 Westwood Boulevard, Suite 420, Los Angeles, CA, 90024, USA.
Lauren SauerUniversity of California, Los Angeles, Department of Medicine - Division of Hematology-Oncology, 924 Westwood Boulevard, Suite 200, Los Angeles, CA, 90024, USA.
Nova F SmedleyUniversity of California, Los Angeles, Department of Bioengineering, 924 Westwood Boulevard, Suite 420, Los Angeles, CA, 90024, USA.
Marshall L SpiegelUniversity of California, Los Angeles, Department of Medicine - Division of Hematology-Oncology, 924 Westwood Boulevard, Suite 200, Los Angeles, CA, 90024, USA.
Jennifer StrunckUniversity of California, Los Angeles, Department of Medicine - Division of Hematology-Oncology, 924 Westwood Boulevard, Suite 200, Los Angeles, CA, 90024, USA.
Edward B GaronUniversity of California, Los Angeles, Department of Medicine - Division of Hematology-Oncology, 924 Westwood Boulevard, Suite 200, Los Angeles, CA, 90024, USA.
Ricky K TairaUniversity of California, Los Angeles, Department of Bioengineering, 924 Westwood Boulevard, Suite 420, Los Angeles, CA, 90024, USA; University of California, Los Angeles, Department of Radiological Sciences, 924 Westwood Boulevard, Suite 420, Los Angeles, CA, 90024, USA.
Denise R AberleUniversity of California, Los Angeles, Department of Bioengineering, 924 Westwood Boulevard, Suite 420, Los Angeles, CA, 90024, USA; University of California, Los Angeles, Department of Radiological Sciences, 924 Westwood Boulevard, Suite 420, Los Angeles, CA, 90024, USA.
Alex A T BuiUniversity of California, Los Angeles, Department of Bioengineering, 924 Westwood Boulevard, Suite 420, Los Angeles, CA, 90024, USA; University of California, Los Angeles, Department of Radiological Sciences, 924 Westwood Boulevard, Suite 420, Los Angeles, CA, 90024, USA.
University of California, Los Angeles · US

Funding

UCLA-Caltech Medical Scientist Training ProgramT32GM008042 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI AJIJOLA, OLUJIMI A, DAWSON, DAVID WAYNE · 1985 to 2023
$29.9M
Training Program for Imaging Based Medical InformaticsT15LM007356 · NLM · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI BUI, ALEX · 2002 to 2011
$5.0M
A model for predicting response to PD-1 inhibitors in NSCLCR01CA208403 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI GARON, EDWARD B · 2017 to 2021
$3.2M
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
Development of a Multimodal Deep Learning Model for the Generation of Cancer Probability Maps and Imaging Biomarkers for Prostate Cancer using Multiparametric MRIF30CA210329 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI SARMA, KARTHIK VENKATARAMAN · 2016 to 2022
$173k
NCI NIH HHS F30 CA210329NCI NIH HHS R01 CA208403NIBIB NIH HHS T32 EB016640NLM NIH HHS R01 LM009961NLM NIH HHS T15 LM007356
6 · The paper itself

Abstract

objectiveIt is crucial for clinicians to stay up to date on current literature in order to apply recent evidence to clinical decision making. Automatic summarization systems can help clinicians quickly view an aggregated summary of literature on a topic. Casama, a representation and summarization system based on "contextualized semantic maps," captures the findings of biomedical studies as well as the contexts associated with patient population and study design. This paper presents a user-oriented evaluation of Casama in comparison to a context-free representation, SemRep. MATERIALS AND

methodsThe effectiveness of the representation was evaluated by presenting users with manually annotated Casama and SemRep summaries of ten articles on driver mutations in cancer. Automatic annotations were evaluated on a collection of articles on EGFR mutation in lung cancer. Seven users completed a questionnaire rating the summarization quality for various topics and applications.

resultsCasama had higher median scores than SemRep for the majority of the topics (p≤ 0.00032), all of the applications (p≤ 0.00089), and in overall summarization quality (p≤ 1.5e-05). Casama's manual annotations outperformed Casama's automatic annotations (p = 0.00061). DISCUSSION: Casama performed particularly well in the representation of strength of evidence, which was highly rated both quantitatively and qualitatively. Users noted that Casama's less granular, more targeted representation improved usability compared to SemRep.

conclusionThis evaluation demonstrated the benefits of a contextualized representation for summarizing biomedical literature on cancer. Iteration on specific areas of Casama's representation, further development of its algorithms, and a clinically-oriented evaluation are warranted.

Indexed as

Decision Making, Computer-AssistedSemanticsComputational BiologyData CurationHumansLung NeoplasmsMutationAutomatic summarizationEvaluationKnowledge representation

Identifiers

PMID29149658
PMCPMC5762403
OpenAlexW2765684156

What OpenQuestion holds

Textmetadata
LicenceTDM
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.