Natural language processing in the molecular imaging domain.

P Karina Tulipano, Ying Tao, Pat Zanzonico, Katherine Kolbert, Yves Lussier, Carol Friedman

Abstract read

In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2005. 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.

Computational approaches to phenotyping: high-throughput phenomics.Proceedings of the American Thoracic Society · 2007
Review

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.

P Karina TulipanoDepartment of Biomedical Informatics, Columbia University, NY, USA.

Ying Tao

Pat Zanzonico

Katherine Kolbert

Yves Lussier

Carol Friedman

Funding

Semantic Approaches to Phenotypic Databases AnalysesK22LM008308 · NLM · UNIVERSITY OF CHICAGO · PI LUSSIER, YVES A · 2004 to 2006

$468k

NLM NIH HHS K22 LM008308

6 · The paper itself

Abstract

Molecular imaging represents the intersection between imaging and genomic sciences. There has been a surge in research literature and information in both sciences. Information contained within molecular imaging literature could be used to 1) link to genomic and imaging information resources and 2) to organize and index images. This research focuses on the adaptation, evaluation, and application of BioMedLEE, a natural language processing system (NLP), in the automated extraction of information from molecular imaging abstracts.

Indexed as

Molecular Diagnostic TechniquesNatural Language ProcessingCell LineComputational BiologyGenesMolecular ProbesMolecular Probes

Identifiers

PMID16779429

PMCPMC1560602

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.