Soft Computing and Medical Bioinformatics

1. Auflage 2019
ISBN: 978-981-13-0058-5
Verlag: Springer Nature Singapore

Buch, Englisch, 139 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 242 g

Reihe: SpringerBriefs in Forensic and Medical Bioinformatics

This book highlights the applications of soft computing techniques in medical bioinformatics. It reflects the state-of-the-art research in soft computing and bioinformatics, including theory, algorithms, numerical simulations, and error and uncertainty analysis. It also deals with novel applications of new processing techniques in computer science. This book is useful to both students and researchers from computer science and engineering fields.

Zielgruppe

Research

Autoren/Hrsg.

Muppalaneni, Naresh Babu

Gurumoorthy, Sasikumar

Ma, Maode

Fachgebiete

• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
• Naturwissenschaften Biowissenschaften Angewandte Biologie Bioinformatik
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Bioinformatik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizinische Mathematik & Informatik

Inhaltsverzeichnis

Cognitive State Classifiers For Identifying Brain Activities.- Classification of Abnormal Blood Vessels in Diabetic Retinopathy using Neural Network.- Design and Implementation of Intelligent System to Detect Malicious Facebook posts using Support Vector Machine (SVM).- A Novel Evolutionary Automatic Clustering Technique by Unifying Initial Seed Selection Algorithms and K-Means into Teaching-Learning-Based Optimization.- A Novel Level Based Dna Security Algorithm Using DNA Codons.- Construction of Breast Cancer Based Protein Protein Interaction Network Using Multiple Sources of Datasets.- Hybridizing spectral clustering with shadow clustering.

Über Autor(innen)

Dr M Naresh Babu is an associate professor at the Department of Computer Science and Systems Engineering, at Sree Vidyanikethan Engineering College in Tirupati, Andhra Pradesh, India. He has edited 2 volumes and published 3 books and more than 18 papers in various international journals and conference proceedings. He is a life member of CSI, member of ISCA, and a senior member of IEEE. His research interests are in the area of computational systems biology, bioinformatics, artificial intelligence in biomedical engineering, applications of intelligent system techniques, image processing, and social network analysis.

Prof. Maode Ma obtained his Ph.D. from the Hong Kong University of Science and Technology in 1999. Currently, he is an associate professor at the School of Electrical and Electronic Engineering at Nanyang Technological University in Singapore. His research interests include network security and wireless networking. Dr. Ma has more than 320 international academic publications including over 150 journal papers and 170 conference papers. He has delivered 50 keynote speeches at various international conferences and has chaired over 80 international conferences. Dr. Ma is a fellow of IET, a senior member of the IEEE Communication and Education Societies, and a member of ACM. He is the Chair of the Singapore Chapters of the IEEE Education Society, and the ACM. He was an IEEE Communication Society distinguished lecturer from 2013 to 2016.

Dr. Sasikumar Gurumurthy is a professor at the Department of Computer Science and Systems Engineering, at Sree Vidhyanikethan Engineering College in Tirupati, Andhra Pradesh, India. He has published more than 60 papers in various international journals, conference proceedings and edited research volumes. He is a member of 10 international forums including IAENG and CSI. His current interests include soft computing and artificial intelligence in biomedical engineering, human and machine interaction and applications of intelligent system techniques, new user interfaces, brain-based interaction, human-centric computing, fuzzy sets and systems, image processing, cloud computing, content-based learning and social network analysis.