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Discovery of Urinary Proteomic Signature for Differential Diagnosis of Acute Appendicitis
المؤلفون المشاركون
He, Fuchu
Qin, Jun
Zhao, Yinghua
Yang, Lianying
Sun, Changqing
Li, Yang
He, Yangzhige
Zhang, Li
Wang, Guangshun
Men, Xuebo
Sun, Wei
Shi, Tieliu
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-9، 9ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-04-06
دولة النشر
مصر
عدد الصفحات
9
التخصصات الرئيسية
الملخص EN
Acute appendicitis is one of the most common acute abdomens, but the confident preoperative diagnosis is still a challenge.
In order to profile noninvasive urinary biomarkers that could discriminate acute appendicitis from other acute abdomens, we carried out mass spectrometric experiments on urine samples from patients with different acute abdomens and evaluated diagnostic potential of urinary proteins with various machine-learning models.
Firstly, outlier protein pools of acute appendicitis and controls were constructed using the discovery dataset (32 acute appendicitis and 41 control acute abdomens) against a reference set of 495 normal urine samples.
Ten outlier proteins were then selected by feature selection algorithm and were applied in construction of machine-learning models using naïve Bayes, support vector machine, and random forest algorithms.
The models were assessed in the discovery dataset by leave-one-out cross validation and were verified in the validation dataset (16 acute appendicitis and 45 control acute abdomens).
Among the three models, random forest model achieved the best performance: the accuracy was 84.9% in the leave-one-out cross validation of discovery dataset and 83.6% (sensitivity: 81.2%, specificity: 84.4%) in the validation dataset.
In conclusion, we developed a 10-protein diagnostic panel by the random forest model that was able to distinguish acute appendicitis from confusable acute abdomens with high specificity, which indicated the clinical application potential of noninvasive urinary markers in disease diagnosis.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Zhao, Yinghua& Yang, Lianying& Sun, Changqing& Li, Yang& He, Yangzhige& Zhang, Li…[et al.]. 2020. Discovery of Urinary Proteomic Signature for Differential Diagnosis of Acute Appendicitis. BioMed Research International،Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1133526
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Zhao, Yinghua…[et al.]. Discovery of Urinary Proteomic Signature for Differential Diagnosis of Acute Appendicitis. BioMed Research International No. 2020 (2020), pp.1-9.
https://search.emarefa.net/detail/BIM-1133526
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Zhao, Yinghua& Yang, Lianying& Sun, Changqing& Li, Yang& He, Yangzhige& Zhang, Li…[et al.]. Discovery of Urinary Proteomic Signature for Differential Diagnosis of Acute Appendicitis. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1133526
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1133526
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر
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