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首页> 外文期刊>International Journal of Reliable and Quality E-Healthcare >An Artificial Intelligence Approach to Thrombophilia Risk
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An Artificial Intelligence Approach to Thrombophilia Risk

机译：一种人工智能血栓冒险风险的方法

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摘要

Thrombophilia stands for a genetic or an acquired tendency to hypercoagulable states, frequently as venous thrombosis. Venous thromboembolism, represented mainly by deep venous thrombosis and pulmonary embolism, is often a chronic illness, associated with high morbidity and mortality. Therefore, it is crucial to identify the cause of the disease, the most appropriate treatment, the length of treatment or prevent a thrombotic recurrence. This work will focus on the development of a diagnosis decision support system in terms of a formal agenda built on a Logic Programming approach to knowledge representation and reasoning, complemented with a computational framework based on Artificial Neural Networks. The proposed model has been quite accurate in the assessment of thrombophilia predisposition (accuracy close to 95%). Furthermore, the model classified properly the patients that really presented the pathology, as well as classifying the disease absence (sensitivity and specificity higher than 95%).
机译：血栓形成常见的血液血栓形成遗传或获得高凝状态的遗传趋势。主要由深静脉血栓形成和肺栓塞主要代表的静脉血栓栓塞，往往​​是慢性疾病，患有高发病率和死亡率。因此，确定疾病的原因至关重要，最合适的治疗，治疗的长度或预防血栓形成复发。这项工作将侧重于在基于知识表示和推理的逻辑编程方法的正式议程方面开发诊断决策支持系统，与基于人工神经网络的计算框架相辅相成。在评估血栓性易感性（精度接近95％）时，拟议的模型非常准确。此外，该模型适当地分类了真正呈现病理学的患者，以及对疾病的缺失（敏感性和特异性高于95％）。

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