Evidence map›Paper›PMID 38701156›Full record

ArticleJournal of neuromuscular diseases2024

IMPatienT: An Integrated Web Application to Digitize, Process and Explore Multimodal PATIENt daTa.

Corentin Meyer, Norma Beatriz Romero, Teresinha Evangelista, Brunot Cadot, Jocelyn Laporte, Anne Jeannin-Girardon, Pierre Collet, Ali Ayadi, Kirsley Chennen, Olivier Poch

Abstract read
In one paragraph

Article in Journal of neuromuscular diseases, 2024. 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

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

10 authors.

Corentin MeyerComplex Systems and Translational Bioinformatics (CSTB), ICube Laboratory, UMR 7357, University of Strasbourg, Strasbourg, France.
Norma Beatriz RomeroNeuromuscular Morphology Unit, Myology Institute, Reference Center of Neuromuscular Diseases Nord-Est-IDF, GHU Pitié-Salpêtrière, Paris, France.
Teresinha EvangelistaNeuromuscular Morphology Unit, Myology Institute, Reference Center of Neuromuscular Diseases Nord-Est-IDF, GHU Pitié-Salpêtrière, Paris, France.
Brunot CadotSorbonne Université, INSERM, Center for Research in Myology, Myology Institute, GHU Pitié-Salpêtrière, Paris, France.
Jocelyn LaporteDepartment Translational Medicine, IGBMC, CNRS UMR 7104, Illkirch, France.
Anne Jeannin-GirardonComplex Systems and Translational Bioinformatics (CSTB), ICube Laboratory, UMR 7357, University of Strasbourg, Strasbourg, France.
Pierre ColletComplex Systems and Translational Bioinformatics (CSTB), ICube Laboratory, UMR 7357, University of Strasbourg, Strasbourg, France.
Ali AyadiComplex Systems and Translational Bioinformatics (CSTB), ICube Laboratory, UMR 7357, University of Strasbourg, Strasbourg, France.
Kirsley ChennenComplex Systems and Translational Bioinformatics (CSTB), ICube Laboratory, UMR 7357, University of Strasbourg, Strasbourg, France.
Olivier PochComplex Systems and Translational Bioinformatics (CSTB), ICube Laboratory, UMR 7357, University of Strasbourg, Strasbourg, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Medical acts, such as imaging, lead to the production of various medical text reports that describe the relevant findings. This induces multimodality in patient data by combining image data with free-text and consequently, multimodal data have become central to drive research and improve diagnoses. However, the exploitation of patient data is problematic as the ecosystem of analysis tools is fragmented according to the type of data (images, text, genetics), the task (processing, exploration) and domain of interest (clinical phenotype, histology). To address the challenges, we developed IMPatienT (Integrated digital Multimodal PATIENt daTa), a simple, flexible and open-source web application to digitize, process and explore multimodal patient data. IMPatienT has a modular architecture allowing to: (i) create a standard vocabulary for a domain, (ii) digitize and process free-text data, (iii) annotate images and perform image segmentation, (iv) generate a visualization dashboard and provide diagnosis decision support. To demonstrate the advantages of IMPatienT, we present a use case on a corpus of 40 simulated muscle biopsy reports of congenital myopathy patients. As IMPatienT provides users with the ability to design their own vocabulary, it can be adapted to any research domain and can be used as a patient registry for exploratory data analysis. A demo instance of the application is available at https://impatient.lbgi.fr/.

Indexed as

InternetHumansSoftwareartificial intelligencecomputer-assisteddiagnosiselectronic health recordshistologyimage processingMuscular diseases

Identifiers

PMID38701156
PMCPMC11307071

What OpenQuestion holds

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LicenceCC BY-NC
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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.