Measuring the Score Matching of the Pairwise Deoxyribonucleic Acid Sequencing using Neuro-Fuzzy

The proposed model for getting the score matching of the deoxyribonucleic acid (DNA) sequence is introduced; the Neuro-Fuzzy procedure is the strategy actualized in this paper; it is used the collection of biological information of the DNA sequence performing with global and local calculations so as to advance the ideal arrangement; we utilize the pairwise DNA sequence alignment to gauge the score of the likeness, which depend on information gathering from the pairwise DNA series to be embedded into the implicit framework; an adaptive neuro-fuzzy inference system model is reasonable for foreseeing the matching score through the preparation and testing in neural system and the induction fuzzy system in fuzzy logic that accomplishes the outcome in elite execution

The Mechanism of Monitoring and Tracking of Healthcare Systems

This work concerned with e-healthcare that transmit digital medical data through healthcare system. Online monitoring is concentrated on the process of monitoring and tracking of people at home, car, office, and any other location. e-healthcare deals with patients that they are located far from doctor jurisdiction. Healthcare monitoring including measurements of temperature, blood pressure / pulse monitors and ECG, etc. This works deals with the development of monitoring system via adding intelligent system to distinguish the emergency cases. This work try to keep patient data privacy, reduce attack or penetration of data, reduce processing time and at the same time increasing the efficiency of the overall system. The privacy of patient data is critical so this must maintain the confidentiality of information from intrusion

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

Esophageal cancer prediction based on qualitative features using adaptive fuzzy reasoning method

AbstractEsophageal cancer is one of the most common cancers world-wide and also the most common cause of cancer death. In this paper, we present an adaptive fuzzy reasoning algorithm for rule-based systems using fuzzy Petri nets (FPNs), where the fuzzy production rules are represented by FPN. We developed an adaptive fuzzy Petri net (AFPN) reasoning algorithm as a prognostic system to predict the outcome for esophageal cancer based on the serum concentrations of C-reactive protein and albumin as a set of input variables. The system can perform fuzzy reasoning automatically to evaluate the degree of truth of the proposition representing the risk degree value with a weight value to be optimally tuned based on the observed data. In addition, the implementation process for esophageal cancer prediction is fuzzily deducted by the AFPN algorithm. Performance of the composite model is evaluated through a set of experiments. Simulations and experimental results demonstrate the effectiveness and performance of the proposed algorithms. A comparison of the predictive performance of AFPN models with other methods and the analysis of the curve showed the same results with an intuitive behavior of AFPN models

Quantitative modeling of gene networks of biological systems using fuzzy Petri nets and fuzzy sets

Quantitative demonstrating of organic frameworks has turned into an essential computational methodology in the configuration of novel and investigation of existing natural frameworks. Be that as it may, active information that portrays the framework's elements should be known keeping in mind the end goal to get pertinent results with the routine displaying strategies. This information is frequently robust or even difficult to get. Here, we exhibit a model of quantitative fuzzy rational demonstrating approach that can adapt to obscure motor information and hence deliver applicable results despite the fact that dynamic information is fragmented or just dubiously characterized. Besides, the methodology can be utilized as a part of the blend with the current cutting edge quantitative demonstrating strategies just in specific parts of the framework, i.e., where the data are absent. The contextual analysis of the methodology suggested in this paper is performed on the model of nine-quality genes. We propose a kind of FPN model in light of fuzzy sets to manage the quantitative modeling of biological systems. The tests of our model appear that the model is practical and entirely powerful for information impersonation and thinking of fuzzy expert frameworks

A New Approach for Modelling Gene Regulatory Networks Using Fuzzy Petri Nets

Gene Regulatory Networks are models of genes and gene interactions at the expression level. The advent of microarray technology has challenged computer scientists to develop better algorithms for modeling the underlying regulatory relationship in between the genes. Fuzzy system has an ability to search microarray datasets for activator/repressor regulatory relationship. In this paper, we present a fuzzy reasoning model based on the Fuzzy Petri Net. The model considers the regulatory triplets by means of predicting changes in expression level of the target based on input expression level. This method eliminates possible false predictions from the classical fuzzy model thereby allowing a wider search space for inferring regulatory relationship. Through formalization of fuzzy reasoning, we propose an approach to construct a rule-based reasoning system. The experimental results show the proposed approach is feasible and acceptable to predict changes in expression level of the target gene

Metallothionein gene polymorphism is considered to be a risk factor for chronic diseases

Metallothioneins are considered the main proteins to protect the cell from toxins like heavy metals and oxidative stress encoded by the Metallothionein gene. Any mutation in this gene leads to a defect in the function of Metallothionein proteins, leading to an increase in the effect of heavy metals. Reactive oxygen species, the SNP A-G (rs28366003) in promotor of the metallothionein gene converts the A allele to G allele, and therefore decreases the transcription qualification of the Metallothionein gene; the aim of the study is correlation between&nbsp; A-G (rs28366003) polymorphism in promotor of Metallothionein gene and the risk factor as well as detecting the levels of heavy metals in patients with Kidney failure, this study includes 60 persons with Kidney failure and 20 persons as a control group with age gape (30-55) years, the blood sample collects from the subject and separate into two-tube, EDTA tube to extraction the DNA and Gel tube to biochemical test. The result showed that there is a relationship between polymorphism in the promotor of the Metallothionein gene in the site &nbsp;A-G (rs28366003). The distribution of different genotypes is wild A.A. 22 %, hetero AG 25%, and mutant 53% in the patients