Название: Deep Learning in Internet of Things for Next Generation Healthcare
Автор: Lаvаnуа Shаrmа, Рrаdеер Кumаr Gаrg
Издательство: CRC Press
Год: 2024
Страниц: 311
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

This book presents the latest developments in Deep Learning-enabled healthcare tools and technologies and offers practical ideas for using the IoT with Deep Learning (motion-based object data) to deal with human dynamics and challenges including critical application domains, technologies, medical imaging, drug discovery, insurance fraud detection and solutions to handle relevant challenges. This book covers real-time healthcare applications, novel solutions, current open challenges, and the future of Deep Learning for next-generation healthcare. It includes detailed analysis of the utilization of the IoT with Deep Learning and its underlying technologies in critical application areas of emergency departments such as drug discovery, medical imaging, fraud detection, and genomes. Convolutional neural networks (CNNs), in particular, are excellent at extracting hierarchical characteristics from images using Deep Learning models. These models learn to recognize edges, textures, forms, and even intricate patterns inside images in the context of human vision. CNNs may automatically identify pertinent features for IoT applications from unprocessed visual data without the need for explicit feature engineering. The classifcation and recognition of objects is one of the most important uses of Deep Learning and human vision in IoT. Deep Learning models can be taught to identify and categorize objects in frames of pictures or videos. Security (intruder detection), retail (product identifcation), healthcare (medical image analysis), and other felds all make use of these capabilities. Postgraduate students and researchers in the departments of Computer Science, working in the areas of the IoT, Deep Learning, Machine Learning, image processing, Big Data, cloud computing, and remote sensing will find this book useful.

Название: Machine Learning and Deep Learning in Neuroimaging Data Analysis
Автор: Аnithа S. Рillаi, Вindu Меnоn
Издательство: CRC Press
Год: 2024
Страниц: 133
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Machine Learning (ML) and Deep Learning (DL) have become essential tools in healthcare. They are capable of processing enormous amounts of data to find patterns and are also adopted into methods that manage and make sense of healthcare data, either electronic healthcare records or medical imagery. This book explores how ML/DL can assist neurologists in identifying, classifying or predicting neurological problems that require neuroimaging. With the ability to model high-dimensional datasets, supervised learning algorithms can help in relating brain images to behavioral or clinical observations and unsupervised learning can uncover hidden structures/patterns in images. Bringing together Artificial Intelligence (AI) experts as well as medical practitioners, these chapters cover the majority of neuro problems that use neuroimaging for diagnosis, along with case studies and directions for future research.

Название: Applications of Artificial Intelligence in the Healthcare Sector
Автор: Jyoti Prakash Patra, Yogesh Kumar Rathore
Издательство: Nova Science Publishers
Серия: Computer Science, Technology and Applications
Год: 2023
Страниц: 188
Язык: английский
Формат: pdf (true)
Размер: 17.2 MB

This book was constructed with the syllabus of many countries’ universities in mind, so that undergraduate students, postgraduate students, and university researchers can utilize it for their studies. Chapter 1 of the book mainly focuses on the background of Artificial Intelligence and its applications in various fields. Chapter 2 presents the applications of Artificial Intelligence to save lives in rural areas. In Chapter 3, applications of Artificial Intelligence in pharmacies are explored. Chapter 4 is about the use of machine learning algorithms to extract and optimize features from the imaging of a diseased patient. Chapter 5 provides details about the machine learning techniques used to detect lung cancer and pneumonia. Chapter 6 examines applications of deep learning techniques to fight the COVID-19 Pandemic. In Chapter 7, the use of deep autoencoders in the fields of bio-medicine is described with its implementation, and Chapter 8 covers chronic disease diagnosis using Artificial Intelligence and the Internet of Things. The last two chapters, Chapters 9 and 10 give focus to currently available health monitoring devices and possible improvements of their design along with the applications of IoRT (Internet of Robotics Things) in healthcare.

Название: Explainable AI in Healthcare: Unboxing Machine Learning for Biomedicine
Автор: Mehul S Raval, Mohendra Roy, Tolga Kaya
Издательство: CRC Press
Год: 2024
Страниц: 329
Язык: английский
Формат: pdf (true)
Размер: 10.6 MB

This book combines technology and the medical domain. It covers advances in Computer Vision (CV) and Machine Learning (ML) that facilitate automation in diagnostics and therapeutic and preventive health care. The special focus on eXplainable Artificial Intelligence (XAI) uncovers the black box of ML and bridges the semantic gap between the technologists and the medical fraternity. Explainable AI in Healthcare: Unboxing Machine Learning for Biomedicine intends to be a premier reference for practitioners, researchers, and students at basic, intermediary levels and expert levels in Computer Science, electronics and communications, information technology, instrumentation and control, and electrical engineering.

Название: AI and Blockchain in Healthcare
Автор: Вiрin Кumаr Rаi, Gаutаm Кumаr, Viрin Вауаn
Издательство: Springer
Год: 2023
Страниц: 241
Язык: английский
Формат: pdf (true), epub
Размер: 25.0 MB

This book presents state-of-the-art blockchain and AI advances in health care. Healthcare service is increasingly creating the scope for blockchain and AI applications to enter the biomedical and healthcare world. Today, blockchain, AI, ML, and deep learning are affecting every domain. Through its cutting-edge applications, AI and ML are helping transform the healthcare industry for the better. Blockchain is a decentralization communication platform that has the potential to decentralize the way we store data and manage information. Blockchain technology has potential to reduce the role of middleman, one of the most important regulatory actors in our society. Transactions are simultaneously secure and trustworthy due to the use of cryptographic principles. In recent years, blockchain technology has become very trendy and has penetrated different domains, mostly due to the popularity of cryptocurrencies. One field where blockchain technology has tremendous potential is health care, due to the need for a more patient-centric approach in healthcare systems to connect disparate systems and to increase the accuracy of electronic healthcare records (EHRs). In today’s scenario, humankind has entered the domain of the Industrial revolution requirements with advanced tools and techniques. Artificial Intelligence (AI) plays a pivotal role in the simulation of human intelligence to process, especially in computing systems. The performance of AI has various applications to apply in expert systems, natural language processing, speech recognition, machine vision, and more.

Название: Artificial Intelligence of Health-Enabled Spaces
Автор: Fаdi Аl- Тurjmаn
Издательство: CRC Press
Год: 2023
Страниц: 203
Язык: английский
Формат: pdf (true)
Размер: 12.9 MB

Artificial Intelligence of Health-Enabled Spaces (AIoH) has made a number of revolutionary advances in clinical studies that we are aware of. Among these advances, intelligent and medical services are gaining a great deal of interest. Nowadays, AI-powered technologies are not only used in saving lives, but also in our daily life activities in diagnosing, controlling, and even tracking of COVID-19 patients. These AI-powered solutions are expected to communicate with cellular networks smoothly in the next-generation networks (5G/6G and beyond) for more effective/critical medical applications. This will open the door for other interesting research areas. This book focuses on the development and analysis of Artificial Intelligence (AI) model applications across multiple disciplines. AI-based Deep Learning models, fuzzy and hybrid intelligent systems, and intrinsic explainable models are also presented in this book. Some of the fields considered in this smart health-oriented book include AI applications in electrical engineering, biomedical engineering, environmental engineering, computer engineering, education, cyber security, chemistry, pharmacy, molecular biology, and tourism.

Название: Artificial Intelligence for Information Management: A Healthcare Perspective
Автор: K.G. Srinivasa, Siddesh G.M.
Издательство: Springer
Год: 2021
Страниц: 332
Язык: английский
Формат: pdf (true)
Размер: 11.5 MB

Discusses advancements in Artificial Intelligent and Machine Learning techniques. This book discusses the advancements in Artificial Intelligent techniques used in the well-being of human healthcare. It details the techniques used in collection, storage and analysis of data and their usage in different healthcare solutions. It also discusses the techniques of predictive analysis in early diagnosis of critical diseases. The edited book is divided into four parts – part A discusses introduction to Artificial Intelligent and Machine Learning in healthcare; part B highlights different analytical techniques used in healthcare; part C provides various security and privacy mechanisms used in healthcare; and finally, part D exemplifies different tools used in visualization and data analytics.

Название: Big Data and Artificial Intelligence for Healthcare Applications
Автор: Ankur Saxena, Nicolas Brault
Издательство: CRC Press
Год: 2021
Страниц: 287
Язык: английский
Формат: pdf (true)
Размер: 32.6 MB

This book covers a wide range of topics on the role of Artificial Intelligence, Machine Learning, and Big Data for healthcare applications and deals with the ethical issues and concerns associated with it. This book explores the applications in different areas of healthcare and highlights the current research.