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内容由The British Journal of General Practice提供。所有播客内容(包括剧集、图形和播客描述)均由 The British Journal of General Practice 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal
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Predicting psychosis in general practice - opportunities for earlier diagnosis using PRisk

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Manage episode 448593911 series 3310902
内容由The British Journal of General Practice提供。所有播客内容(包括剧集、图形和播客描述)均由 The British Journal of General Practice 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

Today, we’re speaking to Dr Sarah Sullivan, a Senior Research Fellow based within the Centre for Academic Mental Health at the University of Bristol.

Title of paper: External validation of a prognostic model to improve prediction of psychosis in primary care

Available at: https://doi.org/10.3399/BJGP.2024.0017

This paper reports the external validation of the only psychosis risk prediction algorithm to be used in primary care. External validation of prediction algorithms is essential to provide evidence of transportability i.e. that the algorithm can be used outside its training environment. This vital step for prediction algorithms is often missed.

  continue reading

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Manage episode 448593911 series 3310902
内容由The British Journal of General Practice提供。所有播客内容(包括剧集、图形和播客描述)均由 The British Journal of General Practice 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

Today, we’re speaking to Dr Sarah Sullivan, a Senior Research Fellow based within the Centre for Academic Mental Health at the University of Bristol.

Title of paper: External validation of a prognostic model to improve prediction of psychosis in primary care

Available at: https://doi.org/10.3399/BJGP.2024.0017

This paper reports the external validation of the only psychosis risk prediction algorithm to be used in primary care. External validation of prediction algorithms is essential to provide evidence of transportability i.e. that the algorithm can be used outside its training environment. This vital step for prediction algorithms is often missed.

  continue reading

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