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A Machine Learning/AI Cancer Rule-Out Test for the NHS Two Week Wait Pathway

A Machine Learning/AI Cancer Rule-Out Test for the NHS Two Week Wait Pathway
NHS 两周等待途径的机器学习/人工智能癌症排除测试
批准号:
105411
负责人:
金额:
$43.86万
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2019
资助国家:
英国
项目状态:
已结题
起止时间:
2019 至 --

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中文摘要
翻译
“精准测试是一种机器学习/人工智能测试,可以迅速‘排除’由全科医生推荐的可能的癌症诊断的患者。93%的病人被全科医生推荐去做可能的诊断,结果却没有癌症。这是因为“安全第一”的方法意味着大多数癌症都是通过这种方式感染的。然而,对于93%的患者来说,这确实意味着几个月的焦虑和不必要的医学检查。因为这些病人仍然有症状,所以找出他们的问题是很重要的,即使不是癌症。精确定位测试有助于确定没有癌症的患者,这样一旦癌症被安全排除,他们就可以在几天而不是几个月后回到他们的全科医生那里。这也将极大地帮助NHS。2018年,英国有217万名患者以这种方式转诊。这给NHS癌症诊断服务带来了巨大压力,而精准检测可以将这一数字减少50多万。这将减轻NHS服务的压力,让临床医生有更多的时间在癌症患者身上。”
英文摘要
"The PinPoint Test is a machine learning/AI test that can rapidly 'rule out' cancer in patients referred by their GP for possible cancer diagnosis.93% of patients referred by their GP for possible diagnosis turn out to not have cancer. This is because of a 'safety first' approach that means most cancers are caught this way. However, it does mean several months of anxiety and unnecessary medical testing for those 93% of patients. And because those patients still have symptoms, it's important to find out what is wrong with them, even if it isn't cancer.The PinPoint Test helps identify the patients who don't have cancer, so that they can go back to their GP in days rather than months, once cancer is safely ruled out.This will also help the NHS a great deal. In 2018, 2.17 million patients in England were referred this way. This puts a huge strain on NHS cancer diagnostic services, and the PinPoint Test can reduce this number by over 500,000\. This will reduce pressure on NHS services, and free up clinicians to spend more time on the patients who do have cancer."
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海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
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  • 批准号:
  • 项目类别:
    省市级项目
  • 资助金额:
    10.0万元
  • 批准年份:
    2022
  • 负责人:
    Nicola Rosario Napolitano
  • 依托单位:
煤矿安全人机混合群智感知任务的约束动态多目标Q-learning进化分配
  • 批准号:
    --
  • 项目类别:
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  • 资助金额:
    30万元
  • 批准年份:
    2022
  • 负责人:
    吉建娇
  • 依托单位:
基于领弹失效考量的智能弹药编队短时在线Q-learning协同控制机理
  • 批准号:
    62003314
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    24.0万元
  • 批准年份:
    2020
  • 负责人:
    沈剑
  • 依托单位: