Author: Zia Uddin Publisher: Springer Nature ISBN: 3031115341 Category : Medical Languages : en Pages : 139
Book Description
User care at home is a matter of great concern since unforeseen circumstances might occur that affect people's well-being. Technologies that assist people in independent living are essential for enhancing care in a cost-effective and reliable manner. Assisted care applications often demand real-time observation of the environment and the resident’s activities using an event-driven system. As an emerging area of research and development, it is necessary to explore the approaches of the user care system in the literature to identify current practices for future research directions. Therefore, this book is aimed at a comprehensive review of data sources (e.g., sensors) with machine learning for various smart user care systems. To encourage the readers in the field, insights of practical essence of different machine learning algorithms with sensor data (e.g., publicly available datasets) are also discussed. Some code segments are also included to motivate the researchers of the related fields to practically implement the features and machine learning techniques. It is an effort to obtain knowledge of different types of sensor-based user monitoring technologies in-home environments. With the aim of adopting these technologies, research works, and their outcomes are reported. Besides, up to date references are included for the user monitoring technologies with the aim of facilitating independent living. Research that is related to the use of user monitoring technologies in assisted living is very widespread, but it is still consists mostly of limited-scale studies. Hence, user monitoring technology is a very promising field, especially for long-term care. However, monitoring of the users for smart assisted technologies should be taken to the next level with more detailed studies that evaluate and demonstrate their potential to contribute to prolonging the independent living of people. The target of this book is to contribute towards that direction.
Author: Mounir Mokhtari Publisher: Springer ISBN: 3319945238 Category : Computers Languages : en Pages : 326
Book Description
This book constitutes the proceedings of the 16th International Conference on Smart Homes and Health Telematics, ICOST 2018, held in Singapore, Singapore, in July 2018. The theme of this year volume is "Designing a better Future: Urban Assisted Living", focusing on quality of life of dependent people not only in their homes, but also in outdoor living environment to improve mobility and social interaction in the city. The 21 regular papers and 11 short papers included in this volume focus on research in the design, development, deployment and evaluation of smart urban environments, assistive technologies, chronic disease management, coaching and health telematics systems.
Author: Ujjwal Ratan Publisher: Packt Publishing Ltd ISBN: 1804619191 Category : Computers Languages : en Pages : 224
Book Description
Build real-world artificial intelligence apps on AWS to overcome challenges faced by healthcare providers and payers, as well as pharmaceutical, life sciences research, and commercial organizations Key FeaturesLearn about healthcare industry challenges and how machine learning can solve themExplore AWS machine learning services and their applications in healthcare and life sciencesDiscover practical coding instructions to implement machine learning for healthcare and life sciencesBook Description While machine learning is not new, it's only now that we are beginning to uncover its true potential in the healthcare and life sciences industry. The availability of real-world datasets and access to better compute resources have helped researchers invent applications that utilize known AI techniques in every segment of this industry, such as providers, payers, drug discovery, and genomics. This book starts by summarizing the introductory concepts of machine learning and AWS machine learning services. You'll then go through chapters dedicated to each segment of the healthcare and life sciences industry. Each of these chapters has three key purposes -- First, to introduce each segment of the industry, its challenges, and the applications of machine learning relevant to that segment. Second, to help you get to grips with the features of the services available in the AWS machine learning stack like Amazon SageMaker and Amazon Comprehend Medical. Third, to enable you to apply your new skills to create an ML-driven solution to solve problems particular to that segment. The concluding chapters outline future industry trends and applications. By the end of this book, you'll be aware of key challenges faced in applying AI to healthcare and life sciences industry and learn how to address those challenges with confidence. What you will learnExplore the healthcare and life sciences industryFind out about the key applications of AI in different industry segmentsApply AI to medical images, clinical notes, and patient dataDiscover security, privacy, fairness, and explainability best practicesExplore the AWS ML stack and key AI services for the industryDevelop practical ML skills using code and AWS servicesDiscover all about industry regulatory requirementsWho this book is for This book is specifically tailored toward technology decision-makers, data scientists, machine learning engineers, and anyone who works in the data engineering role in healthcare and life sciences organizations. Whether you want to apply machine learning to overcome common challenges in the healthcare and life science industry or are looking to understand the broader industry AI trends and landscape, this book is for you. This book is filled with hands-on examples for you to try as you learn about new AWS AI concepts.
Author: Ian Cleland Publisher: Springer ISBN: 3319264109 Category : Computers Languages : en Pages : 302
Book Description
This book constitutes the refereed proceedings of the 7th International Work-Conference on Ambient Assisted Living, IWAAL 2015, held in Puerto Varas, Chile, in December 2015. The 20 full papers presented with 7 short papers were carefully reviewed and selected from 31 submissions. The focus of the papers is on following topics: ambient assisted living for tele-care and tele-rehabilitation; ambient assisted living environments; behaviour analysis and activity recognition; sensing for health and wellbeing; human interaction and perspectives in ambient assisted living solutions.
Author: Ilker Ozsahin Publisher: Bentham Science Publishers ISBN: 168108872X Category : Computers Languages : en Pages : 316
Book Description
This book provides an ideal foundation for readers to understand the application of artificial intelligence (AI) and machine learning (ML) techniques to expert systems in the healthcare sector. It starts with an introduction to the topic and presents chapters which progressively explain decision-making theory that helps solve problems which have multiple criteria that can affect the outcome of a decision. Key aspects of the subject such as machine learning in healthcare, prediction techniques, mathematical models and classification of healthcare problems are included along with chapters which delve in to advanced topics on data science (deep-learning, artificial neural networks, etc.) and practical examples (influenza epidemiology and retinoblastoma treatment analysis). Key Features: - Introduces readers to the basics of AI and ML in expert systems for healthcare - Focuses on a problem solving approach to the topic - Provides information on relevant decision-making theory and data science used in the healthcare industry - Includes practical applications of AI and ML for advanced readers - Includes bibliographic references for further reading The reference is an accessible source of knowledge on multi-criteria decision-support systems in healthcare for medical consultants, healthcare policy makers, researchers in the field of medical biotechnology, oncology and pharmaceutical research and development.
Author: Hemant Ghayvat Publisher: Springer ISBN: 3319520482 Category : Technology & Engineering Languages : en Pages : 160
Book Description
This book focuses on the development of wellness protocols for smart home monitoring, aiming to forecast the wellness of individuals living in ambient assisted living (AAL) environments. It describes in detail the design and implementation of heterogeneous wireless sensors and networks as applied to data mining and machine learning, which the protocols are based on. Further, it shows how these sensor and actuator nodes are deployed in the home environment, generating real-time data on object usage and other movements inside the home, and therefore demonstrates that the protocols have proven to offer a reliable, efficient, flexible, and economical solution for smart home systems. Documenting the approach from sensor to decision making and information generation, the book addresses various issues concerning interference mitigation, errors, security and large data handling. As such, it offers a valuable resource for researchers, students and practitioners interested in interdisciplinary studies at the intersection of wireless sensing processing, radio communication, the Internet of Things and machine learning, and in how they can be applied to smart home monitoring and assisted living environments.
Author: Mohammad "Sufian" Badar Publisher: Springer Nature ISBN: 3031222067 Category : Science Languages : en Pages : 273
Book Description
This textbook is an introductory guide to applied machine learning, specifically for biology students. It familiarizes biology students with the basics of modern computer science and mathematics and emphasizes the real-world applications of these subjects. The chapters give an overview of computer systems and programming languages to establish a basic understanding of the important concepts in computer systems. Readers are introduced to machine learning and artificial intelligence in the field of bioinformatics, connecting these applications to systems biology, biological data analysis and predictions, and healthcare diagnosis and treatment. This book offers a necessary foundation for more advanced computer-based technologies used in biology, employing case studies, real-world issues, and various examples to guide the reader from the basic prerequisites to machine learning and its applications.
Author: A. Aztiria Publisher: IOS Press ISBN: 1614998043 Category : Computers Languages : en Pages : 184
Book Description
We are moving towards a future where environments respond to human preferences and needs. In this world, smart devices equipped with intelligent features and the capability to sense, communicate with and support humans in daily activities will be unremarkable. We already expect our cars to warn us of hazards, track our location and provide timely route advice, and in future we will speak to simple machines and hold conversations with more complex systems, such as intelligent homes, which will help us to monitor conditions, track routine tasks, and program the heating, lighting, garden watering and entertainment centre. But questions have been raised in recent years as to how intelligent these so called smart systems or ambient intelligence environments really are. This book, State of the Art in AI Applied to Ambient Intelligence, part of the outcome of the Workshop on Artificial Intelligence Techniques for Ambient Intelligence (AITAmI) which has now run for 10 consecutive editions, aims to provide a clear picture of what has been achieved after a decade of discussion. It is representative of the diversity of approaches and issues which are currently being considered, and also indicates those avenues which are the most promising for exploration in the next decade. The book provides all those working in the field with an up-to-date reference where they will find inspiration to create better systems for the society of tomorrow.
Author: Arjun Panesar Publisher: Apress ISBN: 1484237994 Category : Computers Languages : en Pages : 390
Book Description
Explore the theory and practical applications of artificial intelligence (AI) and machine learning in healthcare. This book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare and big data challenges. You’ll discover the ethical implications of healthcare data analytics and the future of AI in population and patient health optimization. You’ll also create a machine learning model, evaluate performance and operationalize its outcomes within your organization. Machine Learning and AI for Healthcare provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of AI applications. These are illustrated through leading case studies, including how chronic disease is being redefined through patient-led data learning and the Internet of Things. What You'll LearnGain a deeper understanding of key machine learning algorithms and their use and implementation within wider healthcare Implement machine learning systems, such as speech recognition and enhanced deep learning/AI Select learning methods/algorithms and tuning for use in healthcare Recognize and prepare for the future of artificial intelligence in healthcare through best practices, feedback loops and intelligent agentsWho This Book Is For Health care professionals interested in how machine learning can be used to develop health intelligence – with the aim of improving patient health, population health and facilitating significant care-payer cost savings.
Author: Mani Khanuja Publisher: Packt Publishing Ltd ISBN: 1803244445 Category : Computers Languages : en Pages : 382
Book Description
Build, train, and deploy large machine learning models at scale in various domains such as computational fluid dynamics, genomics, autonomous vehicles, and numerical optimization using Amazon SageMaker Key FeaturesUnderstand the need for high-performance computing (HPC)Build, train, and deploy large ML models with billions of parameters using Amazon SageMakerLearn best practices and architectures for implementing ML at scale using HPCBook Description Machine learning (ML) and high-performance computing (HPC) on AWS run compute-intensive workloads across industries and emerging applications. Its use cases can be linked to various verticals, such as computational fluid dynamics (CFD), genomics, and autonomous vehicles. This book provides end-to-end guidance, starting with HPC concepts for storage and networking. It then progresses to working examples on how to process large datasets using SageMaker Studio and EMR. Next, you'll learn how to build, train, and deploy large models using distributed training. Later chapters also guide you through deploying models to edge devices using SageMaker and IoT Greengrass, and performance optimization of ML models, for low latency use cases. By the end of this book, you'll be able to build, train, and deploy your own large-scale ML application, using HPC on AWS, following industry best practices and addressing the key pain points encountered in the application life cycle. What you will learnExplore data management, storage, and fast networking for HPC applicationsFocus on the analysis and visualization of a large volume of data using SparkTrain visual transformer models using SageMaker distributed trainingDeploy and manage ML models at scale on the cloud and at the edgeGet to grips with performance optimization of ML models for low latency workloadsApply HPC to industry domains such as CFD, genomics, AV, and optimizationWho this book is for The book begins with HPC concepts, however, it expects you to have prior machine learning knowledge. This book is for ML engineers and data scientists interested in learning advanced topics on using large datasets for training large models using distributed training concepts on AWS, deploying models at scale, and performance optimization for low latency use cases. Practitioners in fields such as numerical optimization, computation fluid dynamics, autonomous vehicles, and genomics, who require HPC for applying ML models to applications at scale will also find the book useful.
Author: Zia Uddin
Author: Mounir Mokhtari
Author: Ujjwal Ratan
Author: Ian Cleland
Author: Ilker Ozsahin
Author: Hemant Ghayvat
Author: Mohammad "Sufian" Badar
Author: A. Aztiria
Author: Arjun Panesar
Author: Mani Khanuja