BACKGROUND Ligamentum flavum hematoma(LFH)can cause compression of the spinal cord or nerve root,which results in neurological symptoms.We report a case of lumbar radicular pain due to LFH following a traffic accident...BACKGROUND Ligamentum flavum hematoma(LFH)can cause compression of the spinal cord or nerve root,which results in neurological symptoms.We report a case of lumbar radicular pain due to LFH following a traffic accident.CASE SUMMARY A 59-year-old man complained of left buttock and lateral thigh pain that was dull in nature after a traffic accident 18 d prior to presentation.Magnetic resonance imaging(MRI),taken 17 d after the traffic accident,revealed a mass lesion at the L4-5 Level.These MRI findings suggested subacute LFH.The patient’s pain was not alleviated with conservative treatment,including oral medication and epidural steroid injection.After a partial-hemilaminectomy and removal of LFH,the patient’s pain completely disappeared.CONCLUSION Because early operation for decompression is important for a good outcome,clinicians should be able to determine LFH from MRI results and be aware of the possibility of LFH,especially in patients with a history of trauma.展开更多
针对目前空管特情处置过程中案例记录利用不足的问题,提出了空管特情案例利用框架,并重点研究了其中的案例特征提取方法。基于TextRank算法提出了融合空管特情领域知识与数据分析的特情案例特征提取算法(Special Situation Case TextRan...针对目前空管特情处置过程中案例记录利用不足的问题,提出了空管特情案例利用框架,并重点研究了其中的案例特征提取方法。基于TextRank算法提出了融合空管特情领域知识与数据分析的特情案例特征提取算法(Special Situation Case TextRank,SSC TextRank)。所提方法利用空管特情领域知识构建领域词典,以提升分词效果,依据风险知识及文本数据分析结果,同时结合层次分析法赋权原理对文本中的特征词进行赋权,以优化各词的初始重要度以及词语重要度权重的计算方法。利用某地区空管局提供的2000年—2019年特情案例验证算法的有效性。结果表明:模型较传统自然语言处理中的关键词提取算法准确率提高了约40%,体现了所提方法在特情案例特征提取方面的有效性和优越性。展开更多
基金Supported by the National Research Foundation of Korea Grant funded by the Korean government,No.NRF-2021R1A2C1013073.
文摘BACKGROUND Ligamentum flavum hematoma(LFH)can cause compression of the spinal cord or nerve root,which results in neurological symptoms.We report a case of lumbar radicular pain due to LFH following a traffic accident.CASE SUMMARY A 59-year-old man complained of left buttock and lateral thigh pain that was dull in nature after a traffic accident 18 d prior to presentation.Magnetic resonance imaging(MRI),taken 17 d after the traffic accident,revealed a mass lesion at the L4-5 Level.These MRI findings suggested subacute LFH.The patient’s pain was not alleviated with conservative treatment,including oral medication and epidural steroid injection.After a partial-hemilaminectomy and removal of LFH,the patient’s pain completely disappeared.CONCLUSION Because early operation for decompression is important for a good outcome,clinicians should be able to determine LFH from MRI results and be aware of the possibility of LFH,especially in patients with a history of trauma.
文摘针对目前空管特情处置过程中案例记录利用不足的问题,提出了空管特情案例利用框架,并重点研究了其中的案例特征提取方法。基于TextRank算法提出了融合空管特情领域知识与数据分析的特情案例特征提取算法(Special Situation Case TextRank,SSC TextRank)。所提方法利用空管特情领域知识构建领域词典,以提升分词效果,依据风险知识及文本数据分析结果,同时结合层次分析法赋权原理对文本中的特征词进行赋权,以优化各词的初始重要度以及词语重要度权重的计算方法。利用某地区空管局提供的2000年—2019年特情案例验证算法的有效性。结果表明:模型较传统自然语言处理中的关键词提取算法准确率提高了约40%,体现了所提方法在特情案例特征提取方面的有效性和优越性。
