Cyranose320电子鼻技术用于呼出气体和尿液检测乳腺癌早期无创诊断研究
early non-invasive detection of breast cancer using exhaled breath and urine analysis
电子鼻技术用于呼出气体和尿液无创分析检测乳腺癌早期研究
or herman-saffar a, zvi boger a,b, shai libson c, david lieberman d, raphael gonen a, yehuda zeiri a,*
a biomedical engineering, ben-gurion university of the negev, beer-sheva 84105, israel
b optimal – industrial neural systems, be'er sheva 84243, israel
c breast health center soroka medical center, ben-gurion university, beer sheva, israel
d pulmonary unit, soroka university medical center and the faculty of health sciences, ben- gurion university of the negev, israel
a b s t r a c t
the main focus of this pilot study is to develop a statistical approach that is suitable to model data obtained by different detection methods. the methods used in this study examine the possibility to detect early breast cancer (bc) by exhaled breath and urine samples analysis. exhaled breath samples were collected from 48 breast cancer patients and 45 healthy women that served as a control group. urine samples were collected from 37 patients who were diagnosed with breast cancer based on
physical or mammography tests prior to any surgery, and from 36 healthy women. two commercial electronic noses (cyranose 320) were used for the exhaled breath analysis. urine samples were analyzed using gas-chromatography mass-spectrometry (gc-ms). statistical analysis of results is based on an artificial neural network (ann) obtained following feature extraction and feature selection processes. the model obtained allows classification of breast cancer patients with an accuracy of 95.2% 7.7% using data of one en, and an accuracy of 85% for the other en and for urine samples. the developed statistical analysis method enables accurate classification of patients as healthy or with bc based on simple non-invasive exhaled breath and a urine sample analysis. this study demonstrates that available commercial enose can be used, provided that the data analysis is carried out using an appropriate scheme.
这项初步研究的主要重点是开发一种适用于不同检测方法获得的数据模型的统计方法。本研究采用的方法是通过呼气和尿液样本分析来检验早期乳腺癌(bc)的可能性。从48名乳腺癌患者和45名健康女性身上采集呼气样本，作为对照组。从37名确诊为乳腺癌的患者身上采集尿液样本。
任何手术前的身体或乳房x光检查，以及36名健康女性。两个商用电子鼻(cyranose320)用于呼气分析。用气相色谱-质谱(gc-ms)分析尿液样品。结果的统计分析是基于人工神经网络(ann)的特征提取和特征选择过程得到的。所获得的模型允许使用一个en的数据对乳腺癌患者进行分类，准确率为95.2%7.7%，对其他en和尿液样本的准确率为85%。开发的统计分析方法能够根据简单的无创呼气和尿液样本分析准确地将患者分类为健康或患有bc。这项研究表明，只要使用适当的方案进行数据分析，就可以使用现有的商业enose。
电动阀门控制器的安装与调整
湛江到武城物流公司,湛江到武城物流专线,湛江至武城货运专线
BXD51-6/K32化工锅炉防爆动力配电箱
南京六合区到闽侯货运专线直达物流_南京六合区到福州闽侯物流公司
东莞虎门镇到石家庄井陉矿区货运专线物流包车_东莞虎门镇到井陉矿区物流公司
Cyranose320电子鼻技术用于呼出气体和尿液检测乳腺癌早期无创诊断研究
四氟弹性带和膨体四氟垫用途有什么区别
信百诺恒温恒湿试验箱符合哪些标准
温州到诏安县货运公司,温州到福建诏安县的物流专线货运部
天津到锦州古塔区物流专线+全境到达_天津到古塔区直达物流公司
关于紫外可见分光光度计的工作原理
快速掌握水平给袋包装机的使用秘诀
海盐到长沙开福区物流公司直达运输,海盐到开福区物流专线
抛丸机 打磨柜配套除尘滤芯 粉尘回收滤芯的具体参数
导热油在线清洗后会影响正常使用？
义乌到海东专线物流[直达运输]_义乌到海东物流专线公司
进行土壤冻干时要注意哪些流程
千亿级蓝海加速爆发 智慧灯杆迎高速增长
iPhone SE3曝光：今年就投产！
如何提高三坐标测量机的测量准确性？
电子鼻技术用于呼出气体和尿液无创分析检测乳腺癌早期研究
or herman-saffar a, zvi boger a,b, shai libson c, david lieberman d, raphael gonen a, yehuda zeiri a,*
a biomedical engineering, ben-gurion university of the negev, beer-sheva 84105, israel
b optimal – industrial neural systems, be'er sheva 84243, israel
c breast health center soroka medical center, ben-gurion university, beer sheva, israel
d pulmonary unit, soroka university medical center and the faculty of health sciences, ben- gurion university of the negev, israel
a b s t r a c t
the main focus of this pilot study is to develop a statistical approach that is suitable to model data obtained by different detection methods. the methods used in this study examine the possibility to detect early breast cancer (bc) by exhaled breath and urine samples analysis. exhaled breath samples were collected from 48 breast cancer patients and 45 healthy women that served as a control group. urine samples were collected from 37 patients who were diagnosed with breast cancer based on
physical or mammography tests prior to any surgery, and from 36 healthy women. two commercial electronic noses (cyranose 320) were used for the exhaled breath analysis. urine samples were analyzed using gas-chromatography mass-spectrometry (gc-ms). statistical analysis of results is based on an artificial neural network (ann) obtained following feature extraction and feature selection processes. the model obtained allows classification of breast cancer patients with an accuracy of 95.2% 7.7% using data of one en, and an accuracy of 85% for the other en and for urine samples. the developed statistical analysis method enables accurate classification of patients as healthy or with bc based on simple non-invasive exhaled breath and a urine sample analysis. this study demonstrates that available commercial enose can be used, provided that the data analysis is carried out using an appropriate scheme.
这项初步研究的主要重点是开发一种适用于不同检测方法获得的数据模型的统计方法。本研究采用的方法是通过呼气和尿液样本分析来检验早期乳腺癌(bc)的可能性。从48名乳腺癌患者和45名健康女性身上采集呼气样本，作为对照组。从37名确诊为乳腺癌的患者身上采集尿液样本。
任何手术前的身体或乳房x光检查，以及36名健康女性。两个商用电子鼻(cyranose320)用于呼气分析。用气相色谱-质谱(gc-ms)分析尿液样品。结果的统计分析是基于人工神经网络(ann)的特征提取和特征选择过程得到的。所获得的模型允许使用一个en的数据对乳腺癌患者进行分类，准确率为95.2%7.7%，对其他en和尿液样本的准确率为85%。开发的统计分析方法能够根据简单的无创呼气和尿液样本分析准确地将患者分类为健康或患有bc。这项研究表明，只要使用适当的方案进行数据分析，就可以使用现有的商业enose。
电动阀门控制器的安装与调整
湛江到武城物流公司,湛江到武城物流专线,湛江至武城货运专线
BXD51-6/K32化工锅炉防爆动力配电箱
南京六合区到闽侯货运专线直达物流_南京六合区到福州闽侯物流公司
东莞虎门镇到石家庄井陉矿区货运专线物流包车_东莞虎门镇到井陉矿区物流公司
Cyranose320电子鼻技术用于呼出气体和尿液检测乳腺癌早期无创诊断研究
四氟弹性带和膨体四氟垫用途有什么区别
信百诺恒温恒湿试验箱符合哪些标准
温州到诏安县货运公司,温州到福建诏安县的物流专线货运部
天津到锦州古塔区物流专线+全境到达_天津到古塔区直达物流公司
关于紫外可见分光光度计的工作原理
快速掌握水平给袋包装机的使用秘诀
海盐到长沙开福区物流公司直达运输,海盐到开福区物流专线
抛丸机 打磨柜配套除尘滤芯 粉尘回收滤芯的具体参数
导热油在线清洗后会影响正常使用？
义乌到海东专线物流[直达运输]_义乌到海东物流专线公司
进行土壤冻干时要注意哪些流程
千亿级蓝海加速爆发 智慧灯杆迎高速增长
iPhone SE3曝光：今年就投产！
如何提高三坐标测量机的测量准确性？