AIM： To study the clinical outcomes of medical therapy in patients with right colonic diverticulitis. METHODS： The records of 189 patients with right colonic diverticulitis which was finally diagnosed by computed to...AIM： To study the clinical outcomes of medical therapy in patients with right colonic diverticulitis. METHODS： The records of 189 patients with right colonic diverticulitis which was finally diagnosed by computed tomography, ultrasonography, or operative findings were retrospectively reviewed. RESULTS： Of the 189 patients hospitalized for right colonic diverticulitis, the stages of diverticulitis by a modified Hinchey classification were 26 patients （13.8%） in stage 0, 139 patients （73.5%） in stage I a, 23 patients （12.2%） in stage I b, and 1 patient （0.5%） in stage Ⅲ. Medical therapy was undertaken in 185 of 189 patients （97.9%）. One hundred and eighty three of 185 patients were successfully treated with bowel rest and antibiotics. Two patients in stage I b required a resection or surgical drainage because of an inadequate response to conservative treatment. Recurrent diverticulitis developed in 15 of 183 patients （8.2%） who responded to medical therapy. All 15 patients who suffered a second attack had uncomplicated diverticulitis, and were successfully treated with medical therapy.CONCLUSION： Our results indicate that right colonic diverticulitis is essentially benign and image-guided conservative treatment is primarily required.展开更多
The major mortality factor relevant to the intestinal tract is the growth of tumorous cells(polyps)in various parts.More specifically,colonic polyps have a high rate and are recognized as a precursor of colon cancer g...The major mortality factor relevant to the intestinal tract is the growth of tumorous cells(polyps)in various parts.More specifically,colonic polyps have a high rate and are recognized as a precursor of colon cancer growth.Endoscopy is the conventional technique for detecting colon polyps,and considerable research has proved that automated diagnosis of image regions that might have polyps within the colon might be used to help experts for decreasing the polyp miss rate.The automated diagnosis of polyps in a computer-aided diagnosis(CAD)method is implemented using statistical analysis.Nowadays,Deep Learning,particularly throughConvolution Neural networks(CNN),is broadly employed to allowthe extraction of representative features.This manuscript devises a new Northern Goshawk Optimization with Transfer Learning Model for Colonic Polyp Detection and Classification(NGOTL-CPDC)model.The NGOTL-CPDC technique aims to investigate endoscopic images for automated colonic polyp detection.To accomplish this,the NGOTL-CPDC technique comprises of adaptive bilateral filtering(ABF)technique as a noise removal process and image pre-processing step.Besides,the NGOTL-CPDC model applies the Faster SqueezeNet model for feature extraction purposes in which the hyperparameter tuning process is performed using the NGO optimizer.Finally,the fuzzy Hopfield neural network(FHNN)method can be employed for colonic poly detection and classification.A widespread simulation analysis is carried out to ensure the improved outcomes of the NGOTL-CPDC model.The comparison study demonstrates the enhancements of the NGOTL-CPDC model on the colonic polyp classification process on medical test images.展开更多
Colon cancer is the third most commonly diagnosed cancer in the world.Most colon AdenoCArcinoma(ACA)arises from pre-existing benign polyps in the mucosa of the bowel.Thus,detecting benign at the earliest helps reduce ...Colon cancer is the third most commonly diagnosed cancer in the world.Most colon AdenoCArcinoma(ACA)arises from pre-existing benign polyps in the mucosa of the bowel.Thus,detecting benign at the earliest helps reduce the mortality rate.In this work,a Predictive Modeling System(PMS)is developed for the classification of colon cancer using the Horizontal Voting Ensemble(HVE)method.Identifying different patterns inmicroscopic images is essential to an effective classification system.A twelve-layer deep learning architecture has been developed to extract these patterns.The developedHVE algorithm can increase the system’s performance according to the combined models from the last epochs of the proposed architecture.Ten thousand(10000)microscopic images are taken to test the classification performance of the proposed PMS with the HVE method.The microscopic images obtained from the colon tissues are classified intoACAor benign by the proposed PMS.Results prove that the proposed PMS has∼8%performance improvement over the architecture without using the HVE method.The proposed PMS for colon cancer reduces the misclassification rate and attains 99.2%of sensitivity and 99.4%of specificity.The overall accuracy of the proposed PMS is 99.3%,and without using the HVE method,it is only 91.3%.展开更多
Independent component analysis （ICA） is a widely used method for blind source separation （BSS）. The mature ICA model has a restriction that the number of the sources must equal to that of the sensors used to colle...Independent component analysis （ICA） is a widely used method for blind source separation （BSS）. The mature ICA model has a restriction that the number of the sources must equal to that of the sensors used to collect data, which is hard to meet in most practical cases. In this paper, an overdetermined ICA method is proposed and successfully used in the analysis of human colonic pressure signals. Using principal component analysis （PCA）, the method estimates the number of the sources firstly and reduces the dimensions of the observed signals to the same with that of the sources; and then, Fast- ICA is used to estimate all the sources. From 26 groups of colonic pressure recordings, several colonic motor patterns are extracted, which riot only prove the effectiveness of this method, but also greatly facilitate further medical researches.展开更多
目的:基于医院信息管理系统电子医疗数据,解析真实世界复方苦参注射液治疗结肠恶性肿瘤临床应用特征,为复方苦参注射液的临床合理应用提供参考借鉴。方法:基于中国中医科学院中医临床基础医学研究所建立的医院信息系统电子医疗数据大型...目的:基于医院信息管理系统电子医疗数据,解析真实世界复方苦参注射液治疗结肠恶性肿瘤临床应用特征,为复方苦参注射液的临床合理应用提供参考借鉴。方法:基于中国中医科学院中医临床基础医学研究所建立的医院信息系统电子医疗数据大型集成数据仓库,对来自全国范围22家大型三甲医院使用复方苦参注射液治疗结肠恶性肿瘤的3 328例患者电子医疗数据进行提取,对一般特征、诊断特征、品种用药剂量与疗程特征信息、品种联合用药特征、出院转归特征等进行基于频数与率的描述性分析。结果:使用复方苦参注射液治疗结肠恶性肿瘤的患者平均年龄61.85岁;男性多于女性;主要由消化内科、肿瘤科入院;单次用药剂量以10-20 m L居多;疗程以4-7天为主;临床常见联用药物包括托烷司琼注射液、胸腺肽注射液、奥沙利铂注射液、氟尿嘧啶、亚叶酸钙注射液等;基于出院转归判定的总有效率39.78%。结论:复方苦参注射液治疗结肠恶性肿瘤的人群特征明确,符合结肠恶性肿瘤疾病的一般规律;其真实世界临床用药剂量、疗程范围基本符合品种说明书相关界定。临床联合用药类型较为广泛。展开更多
基金Supported by The research paper scholarship of the graduate school of Kyung Hee University in the second semester of 2007
文摘AIM： To study the clinical outcomes of medical therapy in patients with right colonic diverticulitis. METHODS： The records of 189 patients with right colonic diverticulitis which was finally diagnosed by computed tomography, ultrasonography, or operative findings were retrospectively reviewed. RESULTS： Of the 189 patients hospitalized for right colonic diverticulitis, the stages of diverticulitis by a modified Hinchey classification were 26 patients （13.8%） in stage 0, 139 patients （73.5%） in stage I a, 23 patients （12.2%） in stage I b, and 1 patient （0.5%） in stage Ⅲ. Medical therapy was undertaken in 185 of 189 patients （97.9%）. One hundred and eighty three of 185 patients were successfully treated with bowel rest and antibiotics. Two patients in stage I b required a resection or surgical drainage because of an inadequate response to conservative treatment. Recurrent diverticulitis developed in 15 of 183 patients （8.2%） who responded to medical therapy. All 15 patients who suffered a second attack had uncomplicated diverticulitis, and were successfully treated with medical therapy.CONCLUSION： Our results indicate that right colonic diverticulitis is essentially benign and image-guided conservative treatment is primarily required.
文摘The major mortality factor relevant to the intestinal tract is the growth of tumorous cells(polyps)in various parts.More specifically,colonic polyps have a high rate and are recognized as a precursor of colon cancer growth.Endoscopy is the conventional technique for detecting colon polyps,and considerable research has proved that automated diagnosis of image regions that might have polyps within the colon might be used to help experts for decreasing the polyp miss rate.The automated diagnosis of polyps in a computer-aided diagnosis(CAD)method is implemented using statistical analysis.Nowadays,Deep Learning,particularly throughConvolution Neural networks(CNN),is broadly employed to allowthe extraction of representative features.This manuscript devises a new Northern Goshawk Optimization with Transfer Learning Model for Colonic Polyp Detection and Classification(NGOTL-CPDC)model.The NGOTL-CPDC technique aims to investigate endoscopic images for automated colonic polyp detection.To accomplish this,the NGOTL-CPDC technique comprises of adaptive bilateral filtering(ABF)technique as a noise removal process and image pre-processing step.Besides,the NGOTL-CPDC model applies the Faster SqueezeNet model for feature extraction purposes in which the hyperparameter tuning process is performed using the NGO optimizer.Finally,the fuzzy Hopfield neural network(FHNN)method can be employed for colonic poly detection and classification.A widespread simulation analysis is carried out to ensure the improved outcomes of the NGOTL-CPDC model.The comparison study demonstrates the enhancements of the NGOTL-CPDC model on the colonic polyp classification process on medical test images.
文摘Colon cancer is the third most commonly diagnosed cancer in the world.Most colon AdenoCArcinoma(ACA)arises from pre-existing benign polyps in the mucosa of the bowel.Thus,detecting benign at the earliest helps reduce the mortality rate.In this work,a Predictive Modeling System(PMS)is developed for the classification of colon cancer using the Horizontal Voting Ensemble(HVE)method.Identifying different patterns inmicroscopic images is essential to an effective classification system.A twelve-layer deep learning architecture has been developed to extract these patterns.The developedHVE algorithm can increase the system’s performance according to the combined models from the last epochs of the proposed architecture.Ten thousand(10000)microscopic images are taken to test the classification performance of the proposed PMS with the HVE method.The microscopic images obtained from the colon tissues are classified intoACAor benign by the proposed PMS.Results prove that the proposed PMS has∼8%performance improvement over the architecture without using the HVE method.The proposed PMS for colon cancer reduces the misclassification rate and attains 99.2%of sensitivity and 99.4%of specificity.The overall accuracy of the proposed PMS is 99.3%,and without using the HVE method,it is only 91.3%.
基金supported by National Natural Science Foundation(No.60875061)
文摘Independent component analysis （ICA） is a widely used method for blind source separation （BSS）. The mature ICA model has a restriction that the number of the sources must equal to that of the sensors used to collect data, which is hard to meet in most practical cases. In this paper, an overdetermined ICA method is proposed and successfully used in the analysis of human colonic pressure signals. Using principal component analysis （PCA）, the method estimates the number of the sources firstly and reduces the dimensions of the observed signals to the same with that of the sources; and then, Fast- ICA is used to estimate all the sources. From 26 groups of colonic pressure recordings, several colonic motor patterns are extracted, which riot only prove the effectiveness of this method, but also greatly facilitate further medical researches.
文摘目的:基于医院信息管理系统电子医疗数据,解析真实世界复方苦参注射液治疗结肠恶性肿瘤临床应用特征,为复方苦参注射液的临床合理应用提供参考借鉴。方法:基于中国中医科学院中医临床基础医学研究所建立的医院信息系统电子医疗数据大型集成数据仓库,对来自全国范围22家大型三甲医院使用复方苦参注射液治疗结肠恶性肿瘤的3 328例患者电子医疗数据进行提取,对一般特征、诊断特征、品种用药剂量与疗程特征信息、品种联合用药特征、出院转归特征等进行基于频数与率的描述性分析。结果:使用复方苦参注射液治疗结肠恶性肿瘤的患者平均年龄61.85岁;男性多于女性;主要由消化内科、肿瘤科入院;单次用药剂量以10-20 m L居多;疗程以4-7天为主;临床常见联用药物包括托烷司琼注射液、胸腺肽注射液、奥沙利铂注射液、氟尿嘧啶、亚叶酸钙注射液等;基于出院转归判定的总有效率39.78%。结论:复方苦参注射液治疗结肠恶性肿瘤的人群特征明确,符合结肠恶性肿瘤疾病的一般规律;其真实世界临床用药剂量、疗程范围基本符合品种说明书相关界定。临床联合用药类型较为广泛。
