کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8485084 | 1551696 | 2018 | 25 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Screening for active pulmonary tuberculosis: Development and applicability of artificial neural network models
ترجمه فارسی عنوان
غربالگری سل ریوی فعال: توسعه و کاربرد مدل های شبکه عصبی مصنوعی
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کلمات کلیدی
بیماری سل، سیستم های پشتیبانی تصمیم، تشخیص، مدل شبکه عصبی،
موضوعات مرتبط
علوم زیستی و بیوفناوری
ایمنی شناسی و میکروب شناسی
میکروبیولوژی و بیوتکنولوژی کاربردی
چکیده انگلیسی
Tuberculosis (TB) remains a significant public health challenge, motivated by the diversity of healthcare epidemiological settings, as other factors. Cost-effective screening has substantial importance for TB control, demanding new diagnostic tools. This paper proposes a decision support tool (DST) for screening pulmonary TB (PTB) patients at a secondary clinic. The DST is composed of an adaptive resonance model (iART) for risk group identification (low, medium and high) and a multilayer perceptron (MLP) neural network for classifying patients as active or inactive PTB. Our tool attains an overall sensitivity (SE) and specificity (SP) of 92% (95% CI; 79-97) and 58% (95% CI; 47-68), respectively. SE values for smear-positive and smear-negative patients are 96% (95% CI; 80-99) and 82% (95% CI; 52-95), as well as higher than 83% (95% CI; 43-97) in low and high-risk cases. Even in scenarios with prevalence up to 20%, negative predictive values superior to 95% are obtained. The proposed DST provides a quick and low-cost pretest for presumptive PTB patients, which is useful to guide confirmatory testing and patient management, especially in settings with limited resources in low and middle-incoming countries.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Tuberculosis - Volume 111, July 2018, Pages 94-101
Journal: Tuberculosis - Volume 111, July 2018, Pages 94-101
نویسندگان
João Baptista de Oliveira e Souza Filho, Mauro Sanchez, José Manoel de Seixas, Carmen Maidantchik, Rafael Galliez, Adriana da Silva Rezende Moreira, Paulo Albuquerque da Costa, Martha Maria Oliveira, Anthony David Harries, Afrânio Lineu Kritski,