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Vibrating Particles System Algorithm for Solving Classification Problems

Computer Systems Science & Engineering 2022年第12期43卷 1189-1206页

作者： Mohammad Wedyan Omar Elshaweesh enas ramadan Ryan Alturki Department of Autonomous Systems Faculty of Artificial IntelligenceAl-Balqa Applied UniversityAl-Salt19117Jordan Department of Software Engineering Information Technology CollegeAL-Hussein bin Talal UniversityMa’an71111Jordan Department of Computer Science Prince Abdullah Bin Ghazi Faculty of Communication and Information TechnologyAl-Balqa Applied UniversityAl-Salt19117Jordan Department of Information Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21961Saudi Arabia

Big data is a term that refers to a set of data that,due to its largeness or complexity,cannot be stored or processed with one of the usual tools or applications for data management,and it has become a prominent word in recent years for the massive development of *** immediately thereafter,the term“big data mining”emerged,i.e.,mining from big data even as an emerging and interconnected field of *** is an important stage in data mining since it helps people make better decisions in a variety of situations,including scientific endeavors,biomedical research,and industrial *** probabilistic neural network(PNN)is a commonly used and successful method for handling classification and pattern recognition *** this study,the authors proposed to combine the probabilistic neural network(PPN),which is one of the data mining techniques,with the vibrating particles system(VPS),which is one of the metaheuristic algorithms named“VPS-PNN”,to solve classi-fication problems more *** data set is eleven common benchmark medical datasets from the machine-learning library,the suggested method was *** suggested VPS-PNN mechanism outperforms the PNN,biogeography-based optimization,enhanced-water cycle algorithm(E-WCA)and the firefly algorithm(FA)in terms of convergence speed and classification accuracy.

关键词： Vibrating particles system(VPS) probabilistic neural network(PNN) classification problem data mining

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Prognostic and Clinicopathological Value of the Expression of FOXC2 &YKL-40 in Carcinoma of the Breast, an Immunohistochemical Study

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Advances in Breast Cancer Research 2018年第3期7卷 211-230页

作者： enas M. Fouad Abla S. Mahmoud Rham Z. Ahmed Basant Sh El Shafaay ramadan Mahmoud Gamal Osman Mohamed Farouk Amin Loay M. Gertallah Manar A. Bessar Lecturer of Pathology Faculty of Medicine Zagazig University Zagazig Egypt Lecturer of Pathology Faculty of Medicine Beni-Suef University Cairo Egypt Lecturer of Medical Oncology Faculty of Medicine Zagazig University Zagazig Egypt Lecturer of Clinical Oncology & Nuclear Medicine Faculty of Medicine Zagazig Egypt Lecturer of General Surgery Faculty of Medicine Zagazig University Zagazig Egypt Lecturer of Radiology Faculty of Medicine Zagazig University Zagazig Egypt

Background: Breast cancer is considered the commonest and the most fatal female cancer worldwide. There is to an urgent need for discovering recent therapies to identify patient prognosis and improve treatment strategies. Fork-head Box C2 (FOXC2) is a transcription factor which is a key regulator of cancer stem cells (CSC) properties and epithelial mesenchymal transition (EMT) e.g. cancer initiation, metastatic capacity, and resistance to chemotherapy. FOXC2 roles in CSCs properties and EMT regulation in breast cancer needs detailed studies. YKL-40 is known as chitinase-3-like-1 belongs to a family of mammalian proteins that have an amino acid sequence which is similar to the 18-glycosyl hydrolase bacterial chitinases group. Recent studies have found aberrant YKL-40 elevated expression in cancer of various organs, so it may be used as a recent prognostic biomarker for patients with breast cancer. Former researchers have assessed the expression of FOXC2 & YKL-40 separately in cancer patients and relations to prognosis of patients;however, no studies assessed them together in breast cancer patients and the previous results were inconclusive. Accordingly, our study aimed at evaluation of immunohistochemical expressions of FOXC2 & YKL-40 in carcinoma of the breast in a trial to clarify the relation among their expressions, clinicopathological parameters and recurrence of the disease after successive therapy and patients’ prognosis. Methods: we have evaluated expressions of FOXC2 & YKL-40 in sections from 50 paraffin blocks of carcinoma of the breast using immunohistochemistry. We followed up our patients for 3 years for assessment of recurrence of the disease after successive therapy and survival rates. We analyzed the relationship between their combined expression clinicopathological and prognostic parameters. Results: high FOXC2 expression was associated with older age of the patient (p = 0.002), negative ER (p = 0.009), & PR (p = 0.008), positive HER2neu (p = 0.02),

关键词： Carcinoma of the Breast FOXC2 YKL-40 Prognosis Immunohistochemistry

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