IDIOMS: Infectious Disease Imaging Outbreak Monitoring System
IDIOMS: Infectious Disease Imaging Outbreak Monitoring System
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IDIOMS：传染病成像疫情监测系统
DOI：
10.1145/3428092
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Yesha, Yelena
中科院分区：
文献类型：
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作者：
Gangopadhyay, Aryya;Morris, Michael;Saboury, Babak;Siegel, Eliot;Yesha, Yelena
在这篇评论中，我们提出了一个融合加速器研究的框架，利用AI模型和医学图像来有效诊断、监测和治疗具有大流行潜力的疾病。其目标是创建一种新型的传染病成像爆发监测系统（IDIOMS），以便在患者接受医学成像检查时实时前瞻性地预测、识别和表征患者人群中的潜在传染病爆发。IDIOMS将在疫情被广泛识别之前和在足够的检测资源可用之前提供关键的监测。这可以通过创建传染病医学成像库资源和使用人工智能（AI）实施传染病医学成像分类的计算机视觉方法来实现。通过医学成像改善传染病（ID）的特征可以为复发性疾病提供更早的指标。
In this commentary, we propose a framework for convergence accelerator research leveraging AI models with medical images for effective diagnosis, monitoring, and treatment of diseases with pandemic potential. The goal is to create a novel Infectious Disease Imaging Outbreak Monitoring System (IDIOMS) to prospectively anticipate, identify, and characterize potential infectious disease outbreaks across a population of patients in real-time as patients receive medical imaging examinations. IDIOMS will provide critical surveillance before an outbreak is widely identified and before adequate testing resources are available. This can be achieved through the creation of an infectious disease medical imaging library resource and the implementation of a computer vision approach to infectious disease medical imaging classification using Artificial Intelligence (AI). Improved characterization of Infectious Disease (ID) by medical imaging could provide an earlier indicator for a recurrent