<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Kothari C</submitter><funding>National Center for Advancing Translational Sciences</funding><funding>NICHD NIH HHS</funding><funding>NINDS NIH HHS</funding><funding>National Institutes of Health</funding><pagination>24</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC8943944</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>14(1)</volume><pubmed_abstract>&lt;h4>Background&lt;/h4>Computational phenotypes are most often combinations of patient billing codes that are highly predictive of disease using electronic health records (EHR). In the case of rare diseases that can only be diagnosed by genetic testing, computational phenotypes identify patient cohorts for genetic testing and possible diagnosis. This article details the validation of a computational phenotype for PTEN hamartoma tumor syndrome (PHTS) against the EHR of patients at three collaborating clinical research centers: Boston Children's Hospital, Children's National Hospital, and the University of Washington.&lt;h4>Methods&lt;/h4>A combination of billing codes from the International Classification of Diseases versions 9 and 10 (ICD-9 and ICD-10) for diagnostic criteria postulated by a researc</pubmed_abstract><journal>Journal of neurodevelopmental disorders</journal><pubmed_title>Validation of a computational phenotype for finding patients eligible for genetic testing for pathogenic PTEN variants across three centers.</pubmed_title><pmcid>PMC8943944</pmcid><funding_grant_id>UL1TR001876</funding_grant_id><funding_grant_id>P50 HD105328</funding_grant_id><funding_grant_id>U54HD090257</funding_grant_id><funding_grant_id>K23 NS119666</funding_grant_id><funding_grant_id>U54 HD090257</funding_grant_id><funding_grant_id>U54 HD083091</funding_grant_id><funding_grant_id>P50 HD105351</funding_grant_id><funding_grant_id>U54 HD090255</funding_grant_id><pubmed_authors>Kim D</pubmed_authors><pubmed_authors>Morizono H</pubmed_authors><pubmed_authors>Guay-Woodford L</pubmed_authors><pubmed_authors>Kothari C</pubmed_authors><pubmed_authors>Pomeroy SL</pubmed_authors><pubmed_authors>Good A</pubmed_authors><pubmed_authors>Gallo V</pubmed_authors><pubmed_authors>Geisel G</pubmed_authors><pubmed_authors>Srivastava S</pubmed_authors><pubmed_authors>Izem R</pubmed_authors><pubmed_authors>Gierdalski M</pubmed_authors><pubmed_authors>Sahin M</pubmed_authors><pubmed_authors>Kousa Y</pubmed_authors><pubmed_authors>Dies KA</pubmed_authors><pubmed_authors>Garden GA</pubmed_authors><pubmed_authors>Avillach P</pubmed_authors></additional><is_claimable>false</is_claimable><name>Validation of a computational phenotype for finding patients eligible for genetic testing for pathogenic PTEN variants across three centers.</name><description>&lt;h4>Background&lt;/h4>Computational phenotypes are most often combinations of patient billing codes that are highly predictive of disease using electronic health records (EHR). In the case of rare diseases that can only be diagnosed by genetic testing, computational phenotypes identify patient cohorts for genetic testing and possible diagnosis. This article details the validation of a computational phenotype for PTEN hamartoma tumor syndrome (PHTS) against the EHR of patients at three collaborating clinical research centers: Boston Children's Hospital, Children's National Hospital, and the University of Washington.&lt;h4>Methods&lt;/h4>A combination of billing codes from the International Classification of Diseases versions 9 and 10 (ICD-9 and ICD-10) for diagnostic criteria postulated by a researc</description><dates><release>2022-01-01T00:00:00Z</release><publication>2022 Mar</publication><modification>2026-05-31T05:00:46.389Z</modification><creation>2026-04-08T08:11:45.607Z</creation></dates><accession>S-EPMC8943944</accession><cross_references><pubmed>35321655</pubmed><doi>10.1186/s11689-022-09434-0</doi></cross_references></HashMap>