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You can automatically extract signs and symptoms from medical records by doc2hpo and obtain a ranked list of diseases based on these inputs.

Sharing Cases
PubCaseFinder will support the Phenopackets format, which is ideal for sharing phenotypic data.
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In the future, we plan to provide the capability to save more individual's medically relevant data in Phenopackets format.
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The PubCaseFinder API has been adopted by several patient repositories in the Matchmaker Exchange project.
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In a class at Erasmus Medical Center, one of the largest medical facilities in Europe, PubCaseFinder has been introduced and used for exercises.
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300,000 published case reports included in PubMed are searchable for each disease.

Finding Open-Sharing Cases
You can search about 19,000 open-sharing cases available on the Internet.
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By specifying phenotypes and genes, you can search for open-sharing cases and access their websites.

Filtering Variants
You can prioritize candidate disease-causing genes according to the phenotypic similarity.
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By specifying candidate disease-causing genes in Filter, you can get ranked lists of diseases, genes, and open-sharing case related to the input.

Multilingualization
PubCaseFinder supports English and Japanese. More languages will be supported in the future.
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Please let us know if you have a language you would like support for.
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In the future, we plan to provide a secure feature to manage a set of case records. Individual records can be managed locally by the user.

PubCaseFinder accelerates precision medicine with the phenotype-based resources.

Citation

When you use PubCaseFinder in your publications, please cite:
Fujiwara, T., Yamamoto, Y., Kim, J. D., Buske, O., & Takagi, T. (2018). PubCaseFinder: A case-report-based, phenotype-driven differential-diagnosis system for rare diseases. The American Journal of Human Genetics, 103(3), 389-399.
Yamaguchi, A., Shin, J. M., & Fujiwara, T. (2021, December). Gene Ranking based on Paths from Phenotypes to Genes on Knowledge Graph. IJCKG'21: The 10th International Joint Conference on Knowledge Graphs, 131–134, https://doi.org/10.1145/3502223.3502240
Fujiwara, T., Shin, J. M., & Yamaguchi, A. (2022). Advances in the development of PubCaseFinder, including the new application programming interface and matching algorithm. Human mutation, 43(6), 734–742. https://doi.org/10.1002/humu.24341
