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内容由Oncology Times提供。所有播客内容(包括剧集、图形和播客描述)均由 Oncology Times 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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A Multi-Drug Algorithm Used to Accurately Predict Best First-Line Treatments in Patients With Newly Diagnosed Acute Myeloid Leukemia

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Manage episode 428278268 series 1021077
内容由Oncology Times提供。所有播客内容(包括剧集、图形和播客描述)均由 Oncology Times 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

A mathematical model using data from routine diagnostic samples has been found to accurately predict individual patient responses to the main candidate first-line treatments for acute myeloid leukemia.

Findings from a validation study in independent patient cohorts led by researchers from the Barts Cancer Institute at the Queen Mary University of London were reported at a poster session of the 2024 ASCO Annual Meeting.

Oncology Times correspondent Peter Goodwin attended the session and talked with the second author of the study, Weronika E. Borek PhD, a Bioinformatics Technical Lead at Kinomica Limited in London.

  continue reading

184集单集

Artwork
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Manage episode 428278268 series 1021077
内容由Oncology Times提供。所有播客内容(包括剧集、图形和播客描述)均由 Oncology Times 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

A mathematical model using data from routine diagnostic samples has been found to accurately predict individual patient responses to the main candidate first-line treatments for acute myeloid leukemia.

Findings from a validation study in independent patient cohorts led by researchers from the Barts Cancer Institute at the Queen Mary University of London were reported at a poster session of the 2024 ASCO Annual Meeting.

Oncology Times correspondent Peter Goodwin attended the session and talked with the second author of the study, Weronika E. Borek PhD, a Bioinformatics Technical Lead at Kinomica Limited in London.

  continue reading

184集单集

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