Bioinformatics and medical applications : big data using deep learning algorithms / / edited by A. Suresh [and four others]

• Pubblicazione: Hoboken, NJ : , : Wiley, , ℗2022
• Descrizione fisica: 1 online resource (343 pages)
• Disciplina: 005.7
• Soggetto topico: Medical informatics; Bioinformatics; Big data; Deep learning (Machine learning)
• Persona (resp. second.): SureshA; VimalS; RobinsonY. Harold; RamaswamiDhinesh Kumar; UdendhranR
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Probabilistic Optimization of Machine Learning Algorithms for Heart Disease Prediction / Jaspreet Kaur, Bharti Joshi, Rajashree Shedge -- Cancerous Cells Detection in Lung Organs of Human Body: IoT-Based Healthcare 4.0 Approach / Rohit Rastogi, DK Chaturvedi, Sheelu Sagar, Neeti Tandon, Mukund Rastogi -- Computational Predictors of the Predominant Protein Function: SARS-CoV-2 Case / Carlos Polanco, Manlio F M̀rquez, Gilberto Vargas-Alarc̤n -- Deep Learning in Gait Abnormality Detection: Principles and Illustrations / Saikat Chakraborty, Sruti Sambhavi, Anup Nandy -- Broad Applications of Network Embeddings in Computational Biology, Genomics, Medicine, and Health / Akanksha Jaiswar, Devender Arora, Manisha Malhotra, Abhimati Shukla, Nivedita Rai -- Heart Disease Classification Using Regional Wall Thickness by Ensemble Classifier / J Prakash, Kumar B Vinoth, R Sandhya -- Deep Learning for Medical Informatics and Public Health / K Aditya Shastry, H A Sanjay, M Lakshmi, N Preetham -- An Insight Into Human Pose Estimation and Its Applications / Shambhavi Mishra, Janamejaya Channegowda, Kasina Jyothi Swaroop -- Brain Tumor Analysis Using Deep Learning: Sensor and IoT-Based Approach for Futuristic Healthcare / Rohit Rastogi, DK Chaturvedi, Sheelu Sagar, Neeti Tandon, Akshit Rajan Rastogi -- Study of Emission From Medicinal Woods to Curb Threats of Pollution and Diseases: Global Healthcare Paradigm Shift in 21st Century / Rohit Rastogi, Mamta Saxena, Devendra Kr Chaturvedi, Sheelu Sagar, Neha Gupta, Harshit Gupta, Akshit Rajan Rastogi, Divya Sharma, Manu Bhardwaj, Pranav Sharma -- An Economical Machine Learning Approach for Anomaly Detection in IoT Environment / N Ambika -- Indian Science of Yajna and Mantra to Cure Different Diseases: An Analysis Amidst Pandemic With a Simulated Approach / Rohit Rastogi, Mamta Saxena, Devendra Kumar Chaturvedi, Mayank Gupta, Puru Jain, Rishabh Jain, Mohit Jain, Vishal Sharma, Utkarsh Sangam, Parul Singhal, Priyanshi Garg -- Collection and Analysis of Big Data From Emerging Technologies in Healthcare / K Nagashri, D S Jayalakshmi, J Geetha -- A Complete Overview of Sign Language Recognition and Translation Systems / Kasina Jyothi Swaroop, Janamejaya Channegowda, Shambhavi Mishra -- Index
• Sommario/riassunto: BIOINFORMATICS AND MEDICAL APPLICATIONS The main topics addressed in this book are big data analytics problems in bioinformatics research such as microarray data analysis, sequence analysis, genomics-based analytics, disease network analysis, techniques for big data analytics, and health information technology. Bioinformatics and Medical Applications: Big Data Using Deep Learning Algorithms analyses massive biological datasets using computational approaches and the latest cutting-edge technologies to capture and interpret biological data. The book delivers various bioinformatics computational methods used to identify diseases at an early stage by assembling cutting-edge resources into a single collection designed to enlighten the reader on topics focusing on computer science, mathematics, and biology. In modern biology and medicine, bioinformatics is critical for data management. This book explains the bioinformatician's important tools and examines how they are used to evaluate biological data and advance disease knowledge. The editors have curated a distinguished group of perceptive and concise chapters that presents the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to healthcare. Applying deep learning techniques for data-driven solutions in health information allows automated analysis whose method can be more advantageous in supporting the problems arising from medical and health-related information. Audience The primary audience for the book includes specialists, researchers, postgraduates, designers, experts, and engineers, who are occupied with biometric research and security-related issues.
• Titolo autorizzato: Bioinformatics and medical applications
• ISBN: 1-119-79267-3; 1-119-79266-5
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910830347903321
• Lo trovi qui: Univ. Federico II