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Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications
Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications introduces and explores a variety of schemes designed to empower, enhance, and represent multi-institutional and multi-disciplinary machine learning (ML) and deep learning (DL) research in healthcare paradigms. Serving as a unique compendium of existing and emerging ML/DL paradigms for the healthcare sector, this book demonstrates the depth, breadth, complexity, and diversity of this multi-disciplinary area. It provides a comprehensive overview of ML/DL algorithms and explores the related use cases in enterprises such as computer-aided medical diagnostics, drug discovery and development, medical imaging,...
Machine Learning for Healthcare Applications
When considering the idea of using machine learning in healthcare, it is a Herculean task to present the entire gamut of information in the field of intelligent systems. It is, therefore the objective of this book to keep the presentation narrow and intensive. This approach is distinct from others in that it presents detailed computer simulations for all models presented with explanations of the program code. It includes unique and distinctive chapters on disease diagnosis, telemedicine, medical imaging, smart health monitoring, social media healthcare, and machine learning for COVID-19. These chapters help develop a clear understanding of the working of an algorithm while strengthening logi...
Advances in Information Communication Technology and Computing
The book is a collection of best selected research papers presented at the International Conference on Advances in Information Communication Technology and Computing (AICTC 2021), held in Government Engineering College Bikaner, Bikaner, India, during 20–21 December 2021. The book covers ICT-based approaches in the areas of ICT for energy efficiency, life cycle assessment of ICT, green IT, green information systems, environmental informatics, energy informatics, sustainable HCI or Artificial intelli computational sustainability.
Pattern Recognition and Data Analysis with Applications
This book covers latest advancements in the areas of machine learning, computer vision, pattern recognition, computational learning theory, big data analytics, network intelligence, signal processing and their applications in real world. The topics covered in machine learning involves feature extraction, variants of support vector machine (SVM), extreme learning machine (ELM), artificial neural network (ANN) and other areas in machine learning. The mathematical analysis of computer vision and pattern recognition involves the use of geometric techniques, scene understanding and modelling from video, 3D object recognition, localization and tracking, medical image analysis and so on. Computatio...
Advances in Distributed Computing and Machine Learning
This book includes a collection of peer-reviewed best selected research papers presented at the Third International Conference on Advances in Distributed Computing and Machine Learning (ICADCML 2022), organized by Department of Computer Science and Engineering, National Institute of Technology, Warangal, Telangana, India, during 15–16 January 2022. This book presents recent innovations in the field of scalable distributed systems in addition to cutting edge research in the field of Internet of Things (IoT) and blockchain in distributed environments.
Clinical Cardiology
This book is a comprehensive guide to the diagnosis and treatment of cardiac diseases, for clinicians and trainees. Divided into 14 sections, each one covers a different type of heart disease and is further subdivided to explain the management of more specific disorders within the same disease group. Complete sections are dedicated to diagnostic investigation and imaging techniques including electrocardiography, chest X-ray, and echocardiography. The text is further enhanced by more than 370 clinical images, flowcharts and tables to assist learning and provide quick reference to key facts. Key points Comprehensive guide to diagnosis and management of cardiac diseases Covers many different types of heart disorder Provides thorough discussion on diagnostic imaging and investigation techniques Highly illustrated with more than 370 clinical images, flowcharts and tables
Bedside Cardiology
Bedside Cardiology will appeal to a wide audience of students, teachers, practicing cardiologists and physicians who routinely see patients with cardiac problems. This book presents a selection of over 28 chapters. Each chapter describes how to interpret and formulate a bedside diagnosis, from each and every symptoms and signs in cardiology. Approach is unique because, it is lucid and simple, pragmatic and evidence-based and overall, unbiased.
Machine Learning and Big Data Analytics
This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2022) is intended to be used as a reference book for researchers and professionals to share their research and reports of new technologies and applications in Machine Learning and Big Data Analytics like biometric Recognition Systems, medical diagnosis, industries, telecommunications, AI Petri Nets Model-Based Diagnosis, gaming, stock trading, Intelligent Aerospace Systems, robot control, law, remote sensing and scientific discovery agents and multiagent systems; and natural language and Web intelligence. The intent of this book is to provide awareness of algorithms used for machine learning and big data in the advanced Scientific Technologies, provide a correlation of multidisciplinary areas and become a point of great interest for Data Scientists, systems architects, developers, new researchers and graduate level students. This volume provides cutting-edge research from around the globe on this field. Current status, trends, future directions, opportunities, etc. are discussed, making it friendly for beginners and young researchers.
