مقاله انگلیسی رایگان در مورد سیستم مبتنی بر قوانین باور برای ارزیابی سل – اسپرینگر ۲۰۱۷

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مشخصات مقاله
انتشار مقاله سال ۲۰۱۷
تعداد صفحات مقاله انگلیسی ۱۱ صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
منتشر شده در نشریه اسپرینگر
نوع مقاله ISI
عنوان انگلیسی مقاله A Belief Rule Based Expert System to Assess Tuberculosis under Uncertainty
ترجمه عنوان مقاله سیستم خبره مبتنی بر قوانین باور برای ارزیابی سل تحت شرایط عدم اطمینان
فرمت مقاله انگلیسی  PDF
رشته های مرتبط پزشکی
گرایش های مرتبط پزشکی ریه
مجله مجله سیستم های پزشکی – Journal of Medical Systems
دانشگاه University of Chittagong – Chittagong – Bangladesh
کلمات کلیدی سیستم کارشناس، پایه اعتقادی، عدم قطعیت، بیماری سل، علائم و نشانه ها
کلمات کلیدی انگلیسی Expert system, Belief rule base, Uncertainty, Tuberculosis, Signs and symptoms
شناسه دیجیتال – doi https://doi.org/10.1007/s10916-017-0685-8
کد محصول E8050
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Introduction

Tuberculosis (TB) is considered as one of the life threatening infectious diseases all over the world, usually, caused by the bacterium Mycobacterium tuberculosis. It is usually two types, namely Pulmonary TB (PTB) and Extra-pulmonary TB (ETB). PTB affects lungs, while ETB can attack any organ of the body except brain, spine, heart, pancreas, skeletal striated muscle, and thyroid. The rate of occurrence of PTB is much higher than that of ETB [1–۳]. In 2014, about 9.6 million people became ill and 1.5 million died from TB all over the world. It has been observed that over 95 % death from TB occurs in low and middle income countries. It is considered as one of the top five causes of death for women aged between 15 to 44 [4]. The TB bacteria are usually encapsulated as tiny capsules, called tubercles, in the people with healthy immune system. This stage is known as latent TB. In this stage, the bacteria remain inactive and cannot spread to other people. On the contrary, when people’s immune system becomes weak and hence, it is unable to prevent the growth of bacteria. Eventually, TB becomes active in the human body. Only active pulmonary TB is contagious and the bacteria spread into the air through the cough and sneeze of the affected people. However, ETB is not contagious. In case of PTB nearby people can easily be infected during inhaling. TB can be fatal if it is not treated in time, causing serious complications in the lungs, forming hole between the nearby airways, making breathing difficult because of blocked airways. The primary signs and symptoms of TB are coughing more than three weeks, coughing up blood, fatigue, unintentional weight loss, chest pain, prolonged fever, lack of appetite and night sweating [1–۳]. A physician generally determines the suspicion of TB based on these signs and symptoms. Signs are measured by physician while symptoms are expressed by the patients [5, 6]. Patients usually express the symptoms by using linguistic terms such as high, medium and low, which are imprecise, ambiguous and vague. Therefore, these linguistic terms cannot express the level of symptoms with 100 % certainty and hence, it inherits the types of uncertainty mentioned. In some cases, patients may ignore the importance of coughing since they consider it is related to other common diseases, which is an example of uncertainty due to ignorance. The sputum smear microscopy, which is a method to diagnose the presence of active TB, sometimes it is unable to detect. This is an example of uncertainty due to incompleteness. A comprehensive survey has been carried out in consultation with the physicians of the various TB hospitals, located in Chittagong District of Bangladesh, to identify the types of uncertainties, associated with each of the signs and symptoms of TB, which are described in Table 1. Since the traditional way of determining suspicion of TB is usually carried out by the physicians by looking at the signs and symptoms, it does not consider the above uncertain phenomenon. Thus, the method jeopardizes the accuracy of the detection of TB. However, an expert system which emulates the decision making process of human being can be considered as an appropriate tool to address the uncertain phenomenon to accurately detect the suspicion of TB. An expert system consists of two components, namely knowledge-base and the inference mechanisms. However, such an expert system should have the knowledge representation schema to acquire uncertain clinical knowledge. At the same time, inference mechanism should have the robust reasoning algorithms with the capability to handle various types of uncertainties as mentioned. Therefore, in this study the development of a belief rule-based expert system has been considered, where belief rule base used to handle uncertain knowledge and the evidential reasoning is used as the inference mechanism.

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