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Using LLMs to Help Prevent Pediatric Data Disclosures

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Indhold leveret af Xtelligent Healthcare Media. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Xtelligent Healthcare Media eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

Unintentional disclosures of adolescents’ protected health information are major privacy and security concerns that providers must navigate. Natalie Pageler, MD, chief health informatics officer and division chief of pediatric clinical informatics at Stanford Medicine Children’s Health, discusses how the use of large language models (LLMs) could help prevent these disclosures by identifying confidential content in clinical notes.

  continue reading

120 episoder

Artwork
iconDel
 
Manage episode 419168337 series 2797294
Indhold leveret af Xtelligent Healthcare Media. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Xtelligent Healthcare Media eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

Unintentional disclosures of adolescents’ protected health information are major privacy and security concerns that providers must navigate. Natalie Pageler, MD, chief health informatics officer and division chief of pediatric clinical informatics at Stanford Medicine Children’s Health, discusses how the use of large language models (LLMs) could help prevent these disclosures by identifying confidential content in clinical notes.

  continue reading

120 episoder

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