Leeds Industry Academy: Maximising Engagement with Industry (P2D 2017)

利兹工业学院：最大限度地与工业界互动 (P2D 2017)

• 批准号: MC_PC_17193
• 负责人: Pamela Jones
• 金额: $ 30.24万
• 依托单位: University of Leeds
• 依托单位国家: 英国
• 项目类别: Intramural
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=MC_PC_17193
• 关键词: Leeds; Industry; Academy; Maximising; Engagement

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

目前，所有资助研究的摘要都不能在GTR中找到。这通常是因为在提交提案时并不需要摘要，但可能是因为它包含了个人详细信息等敏感信息。

项目成果

Development and validation of multivariable machine learning algorithms to predict risk of cancer in symptomatic patients referred urgently from primary care: a diagnostic accuracy study.

• DOI: 10.1136/bmjopen-2021-053590
• 发表时间: 2022-04-01
• 期刊: BMJ open
• 影响因子: 2.9
• 作者: Savage R;Messenger M;Neal RD;Ferguson R;Johnston C;Lloyd KL;Neal MD;Sansom N;Selby P;Sharma N;Shinkins B;Skinner JR;Tully G;Duffy S;Hall G
• 通讯作者: Hall G