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PubCaseFinder: A Case-Report-Based, Phenotype-Driven Differential-Diagnosis System for Rare Diseases
Toyofumi Fujiwara1, Yasunori Yamamoto2, Jin-Dong Kim2
1Database 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.
American Journal of Human Genetics
|September 4, 2018
Summary
Text mining rare disease case reports significantly expands disease-phenotype association databases. This improves the accuracy of phenotype-driven differential-diagnosis systems like PubCaseFinder for rare disease diagnosis.
Area of Science:
- Medical Informatics
- Computational Biology
- Rare Disease Research
Background:
- Phenotype-driven systems accelerate rare disease diagnosis.
- System performance depends on comprehensive disease-phenotype association (DPA) databases.
- Manual curation limits DPA database coverage.
Purpose of the Study:
- To enhance DPA database coverage using text mining.
- To improve rare disease differential diagnosis systems.
- To introduce PubCaseFinder, a novel differential diagnosis tool.
Main Methods:
- Developed a text-mining approach to extract DPAs from one million PubMed case reports.
- Integrated automatically extracted DPAs with manually curated DPAs from Orphanet.
- Implemented PubCaseFinder, a web-based, phenotype-driven differential diagnosis system.
Main Results:
- Text mining increased DPA coverage by 125.6% compared to manual curation.
- PubCaseFinder demonstrated improved automated differential diagnosis performance.
- The system facilitates searching and confirming diagnoses using case reports.
Conclusions:
- Text mining is effective for expanding DPA databases for rare diseases.
- PubCaseFinder enhances differential diagnosis by leveraging comprehensive DPA data.
- Automated DPA extraction improves the utility of clinical decision support systems.
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