Artificial Intelligence in Medical Imaging and its Impact on the Rare Disease Community: Threats, Challenges and Opportunities.
Artificial Intelligence in Medical Imaging and its Impact on the Rare Disease Community: Threats, Challenges and Opportunities.
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DOI：
10.1016/j.cpet.2021.09.009
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发表时间：
2022-01
期刊：
影响因子：
2.6
通讯作者：
Saboury B
中科院分区：
文献类型：
--
作者：
Hasani N;Farhadi F;Morris MA;Nikpanah M;Rhamim A;Xu Y;Pariser A;Collins MT;Summers RM;Jones E;Siegel E;Saboury B
几乎十分之一的人可能患有许多罕见疾病（RD）之一。RD患者的平均诊断时间高达7年。如果实施得当，基于人工智能（AI）的正电子发射断层扫描（PET）具有巨大的潜力来推进RD的诊断。如果我们要避免与将AI应用于医疗保健相关的潜在问题，患者倡导团体必须成为AI生态系统中的积极利益相关者。人工智能医疗设备不仅必须在其概念化和生命周期的每个阶段都具有RD意识，而且还应该在代表最终用户群体（包括RD）的多样化和增强的数据集上进行培训。无法做到这一点会导致潜在的伤害，并导致基于人工智能的医疗设备（AIMD）在临床实践中的不可持续部署。
Almost 1 in 10 individuals can suffer from one of many rare diseases (RDs). The average time to diagnosis for an RD patient is as high as 7 years. Artificial intelligence (AI)-based positron emission tomography (PET), if implemented appropriately, has tremendous potential to advance the diagnosis of RDs. Patient advocacy groups must be active stakeholders in the AI ecosystem if we are to avoid potential issues related to the implementation of AI into health care. AI medical devices must not only be RD-aware at each stage of their conceptualization and life cycle but also should be trained on diverse and augmented datasets representative of the end-user population including RDs. Inability to do so leads to potential harm and unsustainable deployment of AI-based medical devices (AIMDs) into clinical practice.
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影响因子：
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