为了快速、准确地对小麦条锈病病害程度进行分级评估,提出了一种基于高光谱成像技术的小麦条锈病病害程度分级方法。首先利用Hyper SIS高光谱成像系统采集受条锈菌侵染后不同发病程度的小麦叶片高光谱图像,通过分析叶片区域与背景的光...为了快速、准确地对小麦条锈病病害程度进行分级评估,提出了一种基于高光谱成像技术的小麦条锈病病害程度分级方法。首先利用Hyper SIS高光谱成像系统采集受条锈菌侵染后不同发病程度的小麦叶片高光谱图像,通过分析叶片区域与背景的光谱特征,对555 nm波长的特征图像进行阈值分割获得掩膜图像,并用掩膜图像对高光谱图像进行掩膜处理,提取仅含叶片的高光谱图像;然后用主成分分析法(Principal component analysis,PCA)得到利于条锈病病斑和健康区域分割的第2主成分(The second principal component,PC2)图像,采用最大类间方差法(Otsu)分割出条锈病病斑区域;最后根据条锈病病斑区域面积占叶片面积的比例对小麦条锈病病害程度进行分级。试验结果表明:测试的270个不同小麦条锈病病害等级的叶片样本中,265个样本可被正确分级,分级正确率为98.15%。该研究为田间小麦条锈病害程度评估提供了基础,也为小麦条锈病抗性鉴定方法提供了新思路。展开更多
Background:Well-known trauma mortality prediction scores such as New Injury Severity Score (NISS), Revised Trauma Score (RTS), and Trauma and Injury Severity Score (TRISS) have been externally validated from high-inco...Background:Well-known trauma mortality prediction scores such as New Injury Severity Score (NISS), Revised Trauma Score (RTS), and Trauma and Injury Severity Score (TRISS) have been externally validated from high-income countries with established trauma databases. However, these scores were never used in Malaysian population. In this current study, we attempted to validate these scoring systems using our regional trauma surgery database. Methods:A retrospective analysis of the regional Malaysian Trauma Surgery Database was performed over a period of 3 years from May 2011 to April 2014. NISS, RTS, Major Trauma Outcome Study (MTOS)-TRISS, and National Trauma Database (NTrD)-TRISS scores were recorded and calculated. Individual scoring system's performance in predicting trauma mortality was compared by calculating the area under the receiver operating characteristic (AUC) curve. Youden index and associated optimal cutoff values for each scoring system was calculated to predict mortality. The corresponding positive predictive value, negative predictive value, and accuracy of the cutoff values were calculated. Results:A total of 2208 trauma patients (2004 blunt and 204 penetrating injuries) with mean age of 36 (SD=16) years were included. There were 239 deaths with a corresponding mortality rate of 10.8%. The AUC calculated for the NISS, RTS, MTOS-TRISS, and NTrD-TRISS were 0.878, 0.802, 0.812, and 0.848, respectively. The NISS score with a cutoff value of 24, sensitivity of 86.6%and specificity of 74.3%, outperformed the rest (p<0.001). Mortality was predicted by NISS with an overall accuracy of 75.6%;its positive predictive value was at 29.02%and negative predictive value at 97.86%. Conclusion:Amongst the four scores, the NISS score is the best trauma mortality prediction model suited for a local Malaysian trauma population. Further validation with multicentre data in the country may require to ascertain the finding.展开更多
目的:针对药品不良反应(adverse drug reaction,ADR)严重程度的评价问题,改进统计法,量化ADR的严重程度,建立新的ADR严重程度分级评价模型。方法:引入区间数学的相关理论,基于Hamming贴近度,提出了ADR严重度和ADR严重程度隶属度的概念,...目的:针对药品不良反应(adverse drug reaction,ADR)严重程度的评价问题,改进统计法,量化ADR的严重程度,建立新的ADR严重程度分级评价模型。方法:引入区间数学的相关理论,基于Hamming贴近度,提出了ADR严重度和ADR严重程度隶属度的概念,结合模糊综合评价法建立新的ADR严重程度分级评价模型。结果:根据新的ADR严重程度分级评价模型,多西他赛的不良反应严重程度为3级,紫杉醇注射液的不良反应严重程度在3级和4级间波动,多西他赛相对紫杉醇注射液严重程度低,严重程度波动相对稳定。结论:基于区间数学和模糊数学理论,变单纯计次为考虑多源信息的模糊计次,能更好地分析利用不良反应报告,并对ADR的严重程度进行量化研究和分级评价,确定ADR的严重程度等级,便于不同药品之间ADR严重程度的比较。展开更多
目的探讨将胰十二指肠切除术(PD)术后B级胰瘘按严重程度分级的可行性。方法回顾性分析2012年12月至2016年6月于哈尔滨医科大学附属第一医院收治的343例行PD病人的临床资料;其中术后发生B级胰瘘72例。按B级胰瘘是否需影像学辅助介入治疗...目的探讨将胰十二指肠切除术(PD)术后B级胰瘘按严重程度分级的可行性。方法回顾性分析2012年12月至2016年6月于哈尔滨医科大学附属第一医院收治的343例行PD病人的临床资料;其中术后发生B级胰瘘72例。按B级胰瘘是否需影像学辅助介入治疗分为重度组(16例)和轻度组(56例);比较组间医疗总费用、住院时间、入重症监护(ICU)率、引流管留置时间、腹腔积液、腹腔感染、腹腔出血、胆瘘、胃排空延迟、胰瘘外其他并发症类型数及发生率、胰瘘为最严重并发症发生率、术后并发症指数(PMI)、胰瘘(ACB)等指标。结果两组间在医疗总费用(8.4万元vs. 13.2万元)、住院时间(29.0 d vs. 42.0 d)、引流管留置时间(20.5 d vs. 53.0 d)、腹腔积液发生率(41.1% vs. 87.5%)、腹腔感染发生率(10.7% vs. 43.8%)、腹腔出血发生率(7.1% vs. 56.3%)、非胰瘘并发症类型数(1种vs. 4种)、胰瘘为最严重并发症发生率(53.6% vs. 87.5%)、PMI(0.22±0.08 vs. 0.37±0.00)、胰瘘ACB(0.19±0.08 vs. 0.37±0.00)差异具有统计学意义(P均<0.05);在胆漏、胃排空延迟、入ICU率、胰瘘外其他并发症发生率上差异无统计学意义。结论在国际胰腺外科研究小组2016版胰瘘分级标准中B级胰瘘严重程度存在异质性;可分为轻度与重度;有助于为PD术后B级胰瘘精准化、个体化治疗提供参考。展开更多
文摘为了快速、准确地对小麦条锈病病害程度进行分级评估,提出了一种基于高光谱成像技术的小麦条锈病病害程度分级方法。首先利用Hyper SIS高光谱成像系统采集受条锈菌侵染后不同发病程度的小麦叶片高光谱图像,通过分析叶片区域与背景的光谱特征,对555 nm波长的特征图像进行阈值分割获得掩膜图像,并用掩膜图像对高光谱图像进行掩膜处理,提取仅含叶片的高光谱图像;然后用主成分分析法(Principal component analysis,PCA)得到利于条锈病病斑和健康区域分割的第2主成分(The second principal component,PC2)图像,采用最大类间方差法(Otsu)分割出条锈病病斑区域;最后根据条锈病病斑区域面积占叶片面积的比例对小麦条锈病病害程度进行分级。试验结果表明:测试的270个不同小麦条锈病病害等级的叶片样本中,265个样本可被正确分级,分级正确率为98.15%。该研究为田间小麦条锈病害程度评估提供了基础,也为小麦条锈病抗性鉴定方法提供了新思路。
文摘Background:Well-known trauma mortality prediction scores such as New Injury Severity Score (NISS), Revised Trauma Score (RTS), and Trauma and Injury Severity Score (TRISS) have been externally validated from high-income countries with established trauma databases. However, these scores were never used in Malaysian population. In this current study, we attempted to validate these scoring systems using our regional trauma surgery database. Methods:A retrospective analysis of the regional Malaysian Trauma Surgery Database was performed over a period of 3 years from May 2011 to April 2014. NISS, RTS, Major Trauma Outcome Study (MTOS)-TRISS, and National Trauma Database (NTrD)-TRISS scores were recorded and calculated. Individual scoring system's performance in predicting trauma mortality was compared by calculating the area under the receiver operating characteristic (AUC) curve. Youden index and associated optimal cutoff values for each scoring system was calculated to predict mortality. The corresponding positive predictive value, negative predictive value, and accuracy of the cutoff values were calculated. Results:A total of 2208 trauma patients (2004 blunt and 204 penetrating injuries) with mean age of 36 (SD=16) years were included. There were 239 deaths with a corresponding mortality rate of 10.8%. The AUC calculated for the NISS, RTS, MTOS-TRISS, and NTrD-TRISS were 0.878, 0.802, 0.812, and 0.848, respectively. The NISS score with a cutoff value of 24, sensitivity of 86.6%and specificity of 74.3%, outperformed the rest (p<0.001). Mortality was predicted by NISS with an overall accuracy of 75.6%;its positive predictive value was at 29.02%and negative predictive value at 97.86%. Conclusion:Amongst the four scores, the NISS score is the best trauma mortality prediction model suited for a local Malaysian trauma population. Further validation with multicentre data in the country may require to ascertain the finding.
文摘目的:针对药品不良反应(adverse drug reaction,ADR)严重程度的评价问题,改进统计法,量化ADR的严重程度,建立新的ADR严重程度分级评价模型。方法:引入区间数学的相关理论,基于Hamming贴近度,提出了ADR严重度和ADR严重程度隶属度的概念,结合模糊综合评价法建立新的ADR严重程度分级评价模型。结果:根据新的ADR严重程度分级评价模型,多西他赛的不良反应严重程度为3级,紫杉醇注射液的不良反应严重程度在3级和4级间波动,多西他赛相对紫杉醇注射液严重程度低,严重程度波动相对稳定。结论:基于区间数学和模糊数学理论,变单纯计次为考虑多源信息的模糊计次,能更好地分析利用不良反应报告,并对ADR的严重程度进行量化研究和分级评价,确定ADR的严重程度等级,便于不同药品之间ADR严重程度的比较。
文摘目的探讨将胰十二指肠切除术(PD)术后B级胰瘘按严重程度分级的可行性。方法回顾性分析2012年12月至2016年6月于哈尔滨医科大学附属第一医院收治的343例行PD病人的临床资料;其中术后发生B级胰瘘72例。按B级胰瘘是否需影像学辅助介入治疗分为重度组(16例)和轻度组(56例);比较组间医疗总费用、住院时间、入重症监护(ICU)率、引流管留置时间、腹腔积液、腹腔感染、腹腔出血、胆瘘、胃排空延迟、胰瘘外其他并发症类型数及发生率、胰瘘为最严重并发症发生率、术后并发症指数(PMI)、胰瘘(ACB)等指标。结果两组间在医疗总费用(8.4万元vs. 13.2万元)、住院时间(29.0 d vs. 42.0 d)、引流管留置时间(20.5 d vs. 53.0 d)、腹腔积液发生率(41.1% vs. 87.5%)、腹腔感染发生率(10.7% vs. 43.8%)、腹腔出血发生率(7.1% vs. 56.3%)、非胰瘘并发症类型数(1种vs. 4种)、胰瘘为最严重并发症发生率(53.6% vs. 87.5%)、PMI(0.22±0.08 vs. 0.37±0.00)、胰瘘ACB(0.19±0.08 vs. 0.37±0.00)差异具有统计学意义(P均<0.05);在胆漏、胃排空延迟、入ICU率、胰瘘外其他并发症发生率上差异无统计学意义。结论在国际胰腺外科研究小组2016版胰瘘分级标准中B级胰瘘严重程度存在异质性;可分为轻度与重度;有助于为PD术后B级胰瘘精准化、个体化治疗提供参考。
