Acute coronary syndrome (ACS) is responsible for the obstruction of coronary arteries, resulting in the loss of lives. The onset of ACS can be determined by looking at the various signs and symptoms of a patient. However, the accuracy of ACS determination is often put into question since there exist different types of uncertainties with the signs and symptoms. Belief rule-based expert systems (BRBESs) are widely used to capture uncertain knowledge and to accomplish the task of reasoning under uncertainty by employing belief rule base and evidential reasoning. This article presents the process of developing a BRBES to determine ACS predictability. The BRBES has been validated against the data of 250 patients suffering from chest pain. It is noticed that the outputs created from the BRBES are more dependable than that of the opinion of cardiologists as well as other two expert system tools, namely artificial neural networks and support vector machine. Hence, it can be argued that the BRBES is capable of playing an important role in decision making as well as in avoiding costly laboratory investigations. A procedure to train the system, allowing its enhancement of performance, is also presented.
Data on the nutritional situation and prevalence of micronutrient deficiencies in Azerbaijan are scarce, and knowledge about anemia risk factors is needed for national and regional policymakers. A nationally representative cross-sectional survey was conducted to assess the prevalence of micronutrient deficiencies, over- and undernutrition, and to disentangle determinants of anemia in children and women in Azerbaijan. The survey generated estimates of micronutrient deficiency and growth indicators for children aged 0–59 months of age (6–59 months for blood biomarkers) and non-pregnant women 15–49 years of age. Questionnaire data, anthropometric measurements, and blood samples were collected to assess the prevalence of under- and over-nutrition, anemia, iron deficiency, and iron deficiency anemia, in both groups. In children only, vitamin A deficiency and zinc deficiency were also assessed. In women only, folate and vitamin B12 deficiencies and vitamin A insufficiency were assessed. In total, 3926 household interviews were successfully completed with a response rate of 80.6%. In the 1455 children, infant and young child feeding practices were relatively poor overall; the prevalence of wasting and stunting were 3.1% and 18.0%, respectively; and 14.1% of children were overweight or obese. The prevalence of anemia was 24.2% in 6–59 months old children, the prevalence of iron deficiency was 15.0% in this age group, and the prevalence of iron deficiency anemia was 6.5%. Vitamin A deficiency was found in 8.0% of children, and zinc deficiency was found in 10.7%. Data from 3089 non-pregnant women 15–49 years of age showed that while undernutrition was scarce, 53% were overweight or obese, with increasing prevalence with increasing age. Anemia affected 38.2% of the women, iron deficiency 34.1% and iron deficiency anemia 23.8%. Vitamin A insufficiency was found in 10.5% of women. Folate and vitamin B12 deficiency were somewhat more common, with prevalence rates of 35.0% and 19.7%, respectively. The main risk factors for anemia in children were recent lower respiratory infection, inflammation and iron deficiency. In women, the main risk factors for anemia were iron deficiency and vitamin A insufficiency. Anemia is a public health problem in Azerbaijani children and women, and additional efforts are needed to reduce anemia in both groups.
Lung Cancer which is also known as carcinoma of the lung or pulmonary carcinoma is one kind of fatal lung tumor described by uncontrolled cell growth in the lung tissues. If this tumor left untreated this growth will be spread beyond the lung in the process of metastasis into the nearby tissues or any other parts or organs of the body. Worldwide Lung Cancer is considered as one of the most leading cause of cancer related death in the present time. So, the assessment of lung cancer is a crucial issue. Lung cancer is generally assessed from its signs, symptoms and risk factors by the physicians. However, assessing lung cancer is complex due to the presence of various types of uncertainties such as vagueness, ignorance, imprecision, incompleteness associated with these signs, symptoms and risk factors. The recently developed generic belief rule-based inference methodology by using the evidential reasoning approach (RIMER) has been considered to develop an expert system to assess this disease. The system can deal with various types of uncertainties found in the clinical signs, symptoms and risk factors. The knowledge base of this system has been constructed by taking account of the real patient data as well as with the consultation of the specialists. The practical case studies are provided to test this system. It has been observed that the proposed system is more reliable than from manual system as well as than from fuzzy rule based expert system. Keywords-Belief rule base; uncertainty; lung cancer; expert systemI.
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