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Psychological Approaches to Radiological Training: Assessing cognitive mechanisms underlying medical-image perception and developing a novel training

Psychological Approaches to Radiological Training: Assessing cognitive mechanisms underlying medical-image perception and developing a novel training
放射训练的心理学方法:评估医学图像感知的认知机制并开发新颖的训练
批准号:
2741124
负责人:
金额:
$0.0万
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2022
资助国家:
英国
项目状态:
未结题
起止时间:
2022 至 --

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英文摘要
The proposed research will answer the following questions:1. What are the perceptual and cognitive mechanisms that contribute to radiological errors?2. How effective are human-intervention and artificial intelligence (AI) training protocols in mitigating errors?3. How can a specially tailored medical image database impact diagnostic accuracy?The goal of the proposed work is to make a positive impact on public health through improved accuracy in medical image perception. This research is well aligned with the ESRC's Strategic Research Challenge of Health and Wellbeing: a social science perspective is crucial for understanding the psychological factors that contribute to radiological perception and decision making and for assessing the impacts of cognitive training. In line with ESRC strategic steers, the proposal also straddles other research council remits, including the Medical Research Council. This research programme has the potential to transform radiological training and advance methods in both psychology and computer science as well as their applications. The research users (radiologists) will be involved in all stages of the research, and the findings will ultimately influence policy within the medical community. This work will result in novel radiological training protocols that can be widely implemented. Enhanced radiological accuracy will save the lives of patients with illnesses and improve the wellbeing of healthy patients by avoiding the stress of inaccurate diagnoses.
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Lagrangian origin of geometric approaches to scattering amplitudes
  • 批准号:
    24ZR1450600
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    ALEXANDER OCHIROV
  • 依托单位: