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An Ontology-Based Approach to Estimate the Frequency of Rare Diseases in Narrative-Text Radiology Reports

机译：基于本体论估算叙事文本放射学报告中罕见疾病频率的方法

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This study sought to use ontology-based knowledge to identify patients with rare diseases and to estimate the frequency of those diseases in a large database of radiology reports. Natural language processing methods were applied to 12,377,743 narrarive-text radiology reports of 7,803,811 patients at an academic health system. Using knowledge from the Orphanet Rare Disease Ontology and Radiology Gamuts Ontology, 1,154 of 6,794 rare diseases (17.0%) were observed in a total of 237,840 patients (3.05%). Ninety of 2,129 diseases (4%) with known prevalence less than 1 per 1,000,000 were observed in the database, whereas 100 of 173 diseases (58%) with prevalence greater than 1 per 10,000 were observed; the difference was statistically significant (p<. 00001). Automated ontology-based search of radiology reports can estimate the frequency of rare diseases, and those diseases with higher known prevalence were significantly more likely to appear in radiology reports.

机译：该研究寻求使用基于本体的知识来鉴定患有罕见疾病的患者，并估计大量放射学报告数据库中这些疾病的频率。应用自然语言处理方法在学术卫生系统的7,803,811名患者中施加到12,377,743名叙事文本放射学报告。利用孤儿鸟稀有疾病本体论和放射性域本体论的知识，1,154名罕见的疾病（17.0％），共计237,840名患者（3.05％）。在数据库中观察到九百九十个，患有众所周知的患病率少于1，而在数据库中观察到每1,000,000次少于1，而观察到100名患病率的100个疾病（58％）（58％）。差异是统计学意义（P <。00001）。基于自动的本体论的放射学报告可以估算稀有疾病的频率，并且这些具有较高患病率的疾病显着更容易出现在放射学报告中。

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《MEDINFO》|2017年|xxxvi 679-1403 p.|共5页
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Charles E. Kahn; Jr.;
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An Ontology-Based Approach to Estimate the Frequency of Rare Diseases in Narrative-Text Radiology Reports

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