Evidence map›Paper›PMID 35143083›Full record

ArticleHuman mutation2022

Advances in the development of PubCaseFinder, including the new application programming interface and matching algorithm.

Toyofumi Fujiwara, Jae-Moon Shin, Atsuko Yamaguchi

Open access · hybridAbstract read
In one paragraph

Article in Human mutation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.0field-weighted citation impact, top 28% 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

8 citing papers in PubMed, 11 citations in OpenAlex.

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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

3 authors at 2 institutions in 1 country.

Toyofumi FujiwaraDatabase Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Kashiwa-shi, Chiba-ken, Japan.ORCID 0000-0002-0170-9172
Jae-Moon ShinDatabase Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Kashiwa-shi, Chiba-ken, Japan.
Atsuko YamaguchiGraduate School of Integrative Science and Engineering, Tokyo City University, Setagaya-ku, Tokyo, Japan.ORCID 0000-0001-7538-5337
Research Organization of Information and Systems · JPTokyo City University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over 10,000 rare genetic diseases have been identified, and millions of newborns are affected by severe rare genetic diseases each year. A variety of Human Phenotype Ontology (HPO)-based clinical decision support systems (CDSS) and patient repositories have been developed to support clinicians in diagnosing patients with suspected rare genetic diseases. In September 2017, we released PubCaseFinder (https://pubcasefinder.dbcls.jp), a web-based CDSS that provides ranked lists of genetic and rare diseases using HPO-based phenotypic similarities, where top-listed diseases represent the most likely differential diagnosis. We also developed a Matchmaker Exchange (MME) application programming interface (API) to query PubCaseFinder, which has been adopted by several patient repositories. In this paper, we describe notable updates regarding PubCaseFinder, the GeneYenta matching algorithm implemented in PubCaseFinder, and the PubCaseFinder API. The updated GeneYenta matching algorithm improves the performance of the CDSS automated differential diagnosis function. Moreover, the updated PubCaseFinder and new API empower patient repositories participating in MME and medical professionals to actively use HPO-based resources.

Indexed as

Databases, GeneticSoftwareAlgorithmsHumansInfant, NewbornPhenotypeRare DiseasesAPIHPOmatching algorithmMatchmaker ExchangePubCaseFinder

Identifiers

PMID35143083
PMCPMC9305291
OpenAlexW4220749237

What OpenQuestion holds

Textmetadata
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.