Evidence map›Paper›PMID 33173922›Full record

ArticlemedRxiv : the preprint server for health sciences2020

Automated analysis of lexical features in Frontotemporal Degeneration.

Sunghye Cho, Naomi Nevler, Sharon Ash, Sanjana Shellikeri, David J Irwin, Lauren Massimo, Katya Rascovsky, Christopher Olm, Murray Grossman, Mark Liberman

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2020. 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
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Sunghye ChoLinguistic Data Consortium, University of Pennsylvania, Philadelphia, PA, USA.
Naomi NevlerDepartment of Neurology and Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA, USA.
Sharon AshDepartment of Neurology and Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA, USA.
Sanjana ShellikeriDepartment of Neurology and Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA, USA.
David J IrwinDepartment of Neurology and Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA, USA.
Lauren MassimoDepartment of Neurology and Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA, USA.
Katya RascovskyDepartment of Neurology and Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA, USA.
Christopher OlmDepartment of Neurology and Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA, USA.
Murray GrossmanDepartment of Neurology and Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA, USA.
Mark LibermanLinguistic Data Consortium, University of Pennsylvania, Philadelphia, PA, USA.

Funding

Transgenic Mouse Models of Tau PathologiesP01AG017586 · NIA · UNIVERSITY OF PENNSYLVANIA · PI LEE, VIRGINIA M · 2000 to 2021
$37.3M
Understanding Environmental Contributions to Heterogeneity in bvFTD.P01AG066597 · NIA · UNIVERSITY OF PENNSYLVANIA · PI David John Irwin, Corey T McMillan · 2020 to 2026
$18.8M
Spreading Tau Pathology in Non-Amnestic Alzheimer's DiseaseR01AG054519 · NIA · UNIVERSITY OF PENNSYLVANIA · PI Jeffrey S Phillips · 2018 to 2026
$7.4M
Semantic Memory and Language Learning in Alzheimer's Disease and Semantic DementiR01DC013063 · NIDCD · TEMPLE UNIV OF THE COMMONWEALTH · PI James Joseph Reilly · 2014 to 2026
$6.8M
Connectomic imaging in familial and sporadic frontotemporal degenerationU01AG052943 · NIA · UNIVERSITY OF PENNSYLVANIA · PI GORNO TEMPINI, MARIA LUISA, GROSSMAN, MURRAY · 2016 to 2019
$5.9M
Identification of Endophenotypes in the Behavioral-Variant of Frontotemporal DemeK23NS088341 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI IRWIN, DAVID JOHN · 2014 to 2018
$836k
Cognitive and Neural Moderators of Longitudinal Decline in Frontotemporal DegenerationR00AG056054 · NIA · UNIVERSITY OF PENNSYLVANIA · PI MASSIMO, LAUREN M · 2018 to 2020
$747k
Cognitive and Neural Moderators of Longitudinal Decline in Frontotemporal DegenerationK99AG056054 · NIA · PENNSYLVANIA STATE UNIVERSITY, THE · PI MASSIMO, LAUREN M · 2016 to 2017
$192k
NIA NIH HHS K99 AG056054NIA NIH HHS P01 AG017586NIA NIH HHS P01 AG066597NIA NIH HHS R00 AG056054NIA NIH HHS R01 AG054519NIA NIH HHS U01 AG052943NIDCD NIH HHS R01 DC013063NINDS NIH HHS K23 NS088341
6 · The paper itself

Abstract

We implemented an automated analysis of lexical aspects of semi-structured speech produced by healthy elderly controls (n=37) and three patient groups with frontotemporal degeneration (FTD): behavioral variant FTD (n=74), semantic variant primary progressive aphasia (svPPA, n=42), and nonfluent/agrammatic PPA (naPPA, n=22). Based on previous findings, we hypothesized that the three patient groups and controls would differ in the counts of part-of-speech (POS) categories and several lexical measures. With a natural language processing program, we automatically tagged POS categories of all words produced during a picture description task. We further counted the number of

Identifiers

PMID33173922
PMCPMC7654918

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.