Evidence map›Paper›PMID 41189646›Full record

ArticleNAR genomics and bioinformatics2025

ClinFly: an all-in-one method to translate, de-identify, and summarize medical reports in HPO format.

Lucas W Gauthier, Marjolaine Willems, Nicolas Chatron, Camille Cenni, Pierre Meyer, Valentin Ruault, Constance Wells, Enody Gernet, Caroline Dunoyer, Quentin Sabbagh and 3 more

Abstract read
In one paragraph

Article in NAR genomics and bioinformatics, 2025. 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

13 authors.

Lucas W GauthierGenetics Department, AURAGEN, Hospices Civils de Lyon, 69500 Bron, France.ORCID https://orcid.org/0009-0008-2571-5308
Marjolaine WillemsInserm U1183, IRMB, Reference center for congenital anomalies, Clinical Genetic Unit, CHU Montpellier, Univ Montpellier, 34000 Montpellier, France.
Nicolas ChatronGenetics Department, AURAGEN, Hospices Civils de Lyon, 69500 Bron, France.ORCID https://orcid.org/0000-0003-0538-0981
Camille CenniClinical Cytology and Genetics Department, CHU Nîmes Carémeau, Univ Montpellier, 30000 Nîmes, France.
Pierre MeyerDepartment of Pediatric Neurology, CHU Montpellier, PhyMedExp, CNRS, INSERM, Univ Montpellier, 34000 Montpellier, France.
Valentin RuaultInserm U1183, IRMB, Reference center for congenital anomalies, Clinical Genetic Unit, CHU Montpellier, Univ Montpellier, 34000 Montpellier, France.
Constance WellsInserm U1183, IRMB, Reference center for congenital anomalies, Clinical Genetic Unit, CHU Montpellier, Univ Montpellier, 34000 Montpellier, France.
Enody GernetMedical Information Department, CHU Montpellier, 34000 Montpellier, France.
Caroline DunoyerMedical Information Department, CHU Montpellier, 34000 Montpellier, France.
Quentin SabbaghInserm U1183, IRMB, Reference center for congenital anomalies, Clinical Genetic Unit, CHU Montpellier, Univ Montpellier, 34000 Montpellier, France.
Claire BardelNGS-HCL Platform, Bioinformatics Unit, Hospices Civils de Lyon,  69500 Bron, France.ORCID https://orcid.org/0009-0001-7197-8730
David GenevieveInserm U1183, IRMB, Reference center for congenital anomalies, Clinical Genetic Unit, CHU Montpellier, Univ Montpellier, 34000 Montpellier, France.
Kevin YauyClinical Genetic Unit, ERIOS, CHU Montpellier, 34000 Montpellier, France.ORCID https://orcid.org/0000-0001-6901-1670

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genomic medicine relies on precise phenotyping and global data sharing, particularly in the context of rare diseases. However, exchanging medical reports across language barriers remains a major challenge. Manual annotation with the Human Phenotype Ontology (HPO) is also prone to inconsistency and incompleteness, risking the loss of clinically relevant information and potential misdiagnoses. We present ClinFly, an open-source pipeline that automatically de-identifies, translates, and summarizes medical reports into HPO terms, in compliance with health-data privacy standards and FAIR principles. In a multicenter, prospective evaluation, we benchmarked ClinFly against physician annotation for de-identification and phenotypic summarization of 50 non-English medical reports. The method achieved a recall of 99% and precision of 77% for protected health information (PHI) de-identification. For HPO summarization, high-confidence predictions reached a recall of 49% and precision of 92%, improving to 78% recall when including low-confidence terms, with an average of 6.6 HPO terms captured per report. ClinFly enables efficient, automated de-identification of PHI and summarization in HPO format to support genomic medicine across language barriers.

Indexed as

Biological OntologiesSoftwareGenomicsHumansPhenotype

Identifiers

PMID41189646
PMCPMC12582024

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Registered trials

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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.