Evidence map›Paper›PMID 30173820›Full record

ArticleAmerican journal of human genetics2018

PubCaseFinder: A Case-Report-Based, Phenotype-Driven Differential-Diagnosis System for Rare Diseases.

Toyofumi Fujiwara, Yasunori Yamamoto, Jin-Dong Kim, Orion Buske, Toshihisa Takagi

Open access · bronzeAbstract read
In one paragraph

Article in American journal of human genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

19 citing papers in PubMed, 44 citations in OpenAlex.

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  18. Rare, rarer, it still has not happened.Croatian medical journal · 2019
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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

5 authors at 3 institutions in 2 countries.

Toyofumi FujiwaraDatabase Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Kashiwa-shi, Chiba-ken 277-0871, Japan; Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa-shi, Chiba-ken 277-8561, Japan. Electronic address: fujiwara@dbcls.rois.ac.jp.
Yasunori YamamotoDatabase Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Kashiwa-shi, Chiba-ken 277-0871, Japan.
Jin-Dong KimDatabase Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Kashiwa-shi, Chiba-ken 277-0871, Japan.
Orion BuskeCentre for Computational Medicine, The Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada.
Toshihisa TakagiDepartment of Biological Sciences, Graduate School of Science, The University of Tokyo, Bunkyo-ku, Tokyo-to, 113-0032, Japan.
Research Organization of Information and Systems · JPThe University of Tokyo · JPHospital for Sick Children · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, to speed up the differential-diagnosis process based on symptoms and signs observed from an affected individual in the diagnosis of rare diseases, researchers have developed and implemented phenotype-driven differential-diagnosis systems. The performance of those systems relies on the quantity and quality of underlying databases of disease-phenotype associations (DPAs). Although such databases are often developed by manual curation, they inherently suffer from limited coverage. To address this problem, we propose a text-mining approach to increase the coverage of DPA databases and consequently improve the performance of differential-diagnosis systems. Our analysis showed that a text-mining approach using one million case reports obtained from PubMed could increase the coverage of manually curated DPAs in Orphanet by 125.6%. We also present PubCaseFinder (see Web Resources), a new phenotype-driven differential-diagnosis system in a freely available web application. By utilizing automatically extracted DPAs from case reports in addition to manually curated DPAs, PubCaseFinder improves the performance of automated differential diagnosis. Moreover, PubCaseFinder helps clinicians search for relevant case reports by using phenotype-based comparisons and confirm the results with detailed contextual information.

Indexed as

Databases, GeneticData MiningDiagnosis, DifferentialHumansPhenotypeRare Diseasescase reportdifferential diagnosisdisease-phenotype associationHuman Phenotype OntologyPubCaseFinderrare disease

Identifiers

PMID30173820
PMCPMC6128307
OpenAlexW2888930188

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.