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July 10, 2026JAMIA OpenOpen Access

Computational phenotyping of sexually transmitted infections with the All of Us Research Program from 2010 to 2023

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Authors

FSFanghui ShiHXHuiyi XiaSWSharon Weissman

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Overview

Randomized trial develops computational algorithms to identify STIs in diverse populations, suggesting improved case detection methods.

Key Points

  • This research aims to create algorithms for accurately identifying sexually transmitted infections (STIs) using EHR data.
  • Developed computational phenotyping algorithms using All of Us Research Program data from May 2018 to October 2023.
  • Analyzed diagnostic codes, laboratory results, and medication records to identify leading STIs: chlamydia, gonorrhea, and syphilis.
  • Examined data from 393,596 participants, focusing on confirmed and presumed STI cases.
  • Confirmed cases: 2603 chlamydia, 1520 gonorrhea, and 2762 syphilis.
  • Identified an additional 4843 possible chlamydia cases and 18,855 possible gonorrhea cases.
  • Notable STI trend shift observed in 2019 with increase from 2010 to 2019, followed by a decline through 2023.

Cite This Study

Shi et al. (2026) studied this question.

synapsesocial.com/papers/6a508e5b6eeac72a437a13edhttps://doi.org/10.1093/jamiaopen/ooag127
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