Artificial Intelligence Approaches for Studying the <em>pp</em> Interactions at High Energy Using Adaptive Neuro-Fuzzy Interface System

Adaptive Neuro-Fuzzy Inference System (ANFIS), a popular machine learning model, is introduced in this chapter. ANFIS has a long development history and good agreement on scientific accomplishments. The value of ANFIS has grown dramatically along with the great interest in deep learning. We will examine how machine learning and ANFIS are related. Different methods can be used to implement machine learning models. ANFIS is a Fuzzy Inference System (FIS) that works within the context of adaptive networks. It merges the ideas of Artificial Neural Networks (ANNs) and Fuzzy Logic (FL) into a single framework. This framework can learn to estimate nonlinear functions and operates as a universal estimator. This chapter aimed to investigate the behavior of D mesons ratios production cross section (D+/D0,D∗+/D0,Ds+/D0,andDs+/D+), differential production cross section of prompt (D0,D+, D∗+andDs+ mesons) as a function of PT in pp collisions at (s = 5.02 and 7 TeV) and predict the behavior for others. The ANFIS model was created through a series of trial-and-error experiments. The ANFIS-based model simulation results perfectly fit the experimental data. When tested with non-training data points, the ANFIS prediction capabilities performed well. The ANFIS offers extensive procedures for high-energy physics modeling

Pattern of congenital malformations in newborn: a hospital-based study

Background: Birth defects, encountered frequently by pediatricians, are important causes of childhood morbidity and mortality. Birth defects can be classified based on their severity, pathogenic mechanism or whether they involve a single system or multiple systems. This hospital based prospective descriptive study highlights the prevalence of congenital anomalies (CAs) in one year, among liveborn neonates delivered in a university hospital. Design and methods: All women giving birth to babies were included. Demographic details, associated risk factors and the type of CAs in babies were recorded. Diagnosis of CAs was based on clinical evaluation, radiographic examination and chromosomal analysis of newborn whenever recommended. Results: The overall incidence of CAs among liveborn neonates was 2.5%, as most of the cases were referred to Zagazig University Hospital for delivery. The musculoskeletal system (23%) was the most commonly involved; followed by central nervous system (20.3%). Involvement of more than one system was observed in (28.6%) cases. Out of the maternal and fetal risk factors, parental consanguinity, maternal undernutrition and obesity, positive history of an anomaly in the family, low birth weight(LBW), and prematurity were significantly associated with higher frequency of CAs(p &amp;lt;0.05), with non-significant differences for maternal age and the sex of the neonates. Conclusion : The current study highlighted the point prevalence of congenital anomalies in one year in zagazig university hospital in Egypt. The present study revealed a high prevalence of congenital anomalies in our locality and stressed upon the importance of carrying out a thorough clinical examination of all neonates at birth

Pattern of Congenital Anomalies in Newborn: A Hospital-Based Study

Birth defects, encountered frequently by pediatricians, are important causes of childhood morbidity and mortality. Birth defects can be classified according to their severity, pathogenic mechanism, or whether they are involving a single system or multiple systems. This hospital-based prospective descriptive study highlights the prevalence of Congenital Anomalies (CAs) in one year among live born neonates delivered in Zagazig University Hospital (Egypt). All women giving birth to viable babies were included. Demographic details, associated risk factors and the type of CAs in all babies were recorded. Diagnosis of CAs was based on clinical evaluation, radiographic examination, ultrasonography, echocardiography and chromosomal analysis of the newborn whenever recommended. The overall incidence of CAs among live born neonates was 2.5%, as most of the cases were referred to Zagazig University Hospital (Egypt) for delivery. The musculoskeletal system (23%) was the most commonly involved followed by the central nervous system (20.3%). Involvement of more than one system was observed in (28.6%) cases. Among maternal and fetal risk factors; parental consanguinity, maternal under nutrition and obesity, positive history of an anomaly in the family, low birth weight, and prematurity were significantly associated with higher frequency of CAs (P&lt;0.05), with non-significant differences for maternal age and the sex of the neonates. The current study highlights the prevalence of congenital anomalies in one year in Zagazig University Hospital. It revealed a high prevalence of congenital anomalies in our locality and stressed the importance of carrying out a thorough clinical examination of all neonates at birth