Enabling Person-Centric Healthcare Using Ambient Assistive Technology Personalized and Patient-Centric Healthcare Services in AAT /
Enabling Person-Centric Healthcare Using Ambient Assistive Technology Personalized and Patient-Centric Healthcare Services in AAT / [electronic resource] :
edited by Paolo Barsocchi, Naga Srinivasu Parvathaneni, Amik Garg, Akash Kumar Bhoi, Filippo Palumbo.
- 1st ed. 2023.
- XII, 317 p. 113 illus., 87 illus. in color. online resource.
- Studies in Computational Intelligence, 1108 1860-9503 ; .
- Studies in Computational Intelligence, 1108 .
Acceso multiusuario
Sensor Datasets for Human Daily Safety and Well-being -- Habitpad: A Habit-Change Person-Centric Healthcare Mobile Application with Machine Leaning and Gamification Features for Obesity -- Human centered Mathematics: a framework for medical applications based on Extended Reality and Artificial Intelligence -- Attentive Vision-Based Model for Sarcopenia Screening by Automating Timed Up-and-Go (TUG) Test -- AAL with Deep Learning to classify the Diseases remotely from the image data -- Heart Failure Prediction Using Radial Basis with Metaheuristic Optimization -- Healthcare Management And Prediction Of Future Illness Through Autonomous Intelligent Advisory System Using Aat Computational Framework -- ResNet-50-CNN and LSTM based Arrhythmia detection model based on ECG dataset -- A Review of Brain-Computer Interface (BCI) System: Advancement and Applications -- Optimized TSA ResNet architecture with TSH -discriminatory features for kidney stone classification from QUS Images -- Ambient Healthcare: A new Paradigm in Medical Zone -- Illuminating Unexplored Corners in Healthcare Space using Ambience Intelligence -- Depression Assessment in Youths using an Enhanced Deep Learning Approach -- Telemedicine Enabled Remote Digital Healthcare System.
This book experiences the future of patient-centered healthcare and dives into the latest advancements and transformative technologies that are revolutionizing the well-being of individuals around the globe. The readers can join authors on an engaging journey as the authors explore the captivating realm of ambient assisted living and unlock its immense potential for improving healthcare outcomes. This book goes beyond mere exploration; it invites readers to embark on a voyage of discovery as authors unveil the outcomes of groundbreaking research ideas. With a diverse range of applications, from deep learning in healthcare to cutting-edge models, the authors offer a comprehensive view of the opportunities and challenges that lie ahead. Whether you're a healthcare professional, an academic seeking the latest insights, or a researcher delving into the realms of ambient assistive technology, biomedical engineering, or computational intelligence, this book is an invaluable resource. Additionally, postgraduate students pursuing data engineering systems find it to be an essential guide. Each chapter stands independently, providing a comprehensive overview of problem formulation and its tangible outcomes. The readers can immerse themselves in the world of patient-centered healthcare today and become part of the forefront of innovation.
9783031382819
Computational intelligence.
Biomedical engineering.
Artificial intelligence.
Computational Intelligence.
Biomedical Engineering and Bioengineering.
Artificial Intelligence.
Q342
006.3
Acceso multiusuario
Sensor Datasets for Human Daily Safety and Well-being -- Habitpad: A Habit-Change Person-Centric Healthcare Mobile Application with Machine Leaning and Gamification Features for Obesity -- Human centered Mathematics: a framework for medical applications based on Extended Reality and Artificial Intelligence -- Attentive Vision-Based Model for Sarcopenia Screening by Automating Timed Up-and-Go (TUG) Test -- AAL with Deep Learning to classify the Diseases remotely from the image data -- Heart Failure Prediction Using Radial Basis with Metaheuristic Optimization -- Healthcare Management And Prediction Of Future Illness Through Autonomous Intelligent Advisory System Using Aat Computational Framework -- ResNet-50-CNN and LSTM based Arrhythmia detection model based on ECG dataset -- A Review of Brain-Computer Interface (BCI) System: Advancement and Applications -- Optimized TSA ResNet architecture with TSH -discriminatory features for kidney stone classification from QUS Images -- Ambient Healthcare: A new Paradigm in Medical Zone -- Illuminating Unexplored Corners in Healthcare Space using Ambience Intelligence -- Depression Assessment in Youths using an Enhanced Deep Learning Approach -- Telemedicine Enabled Remote Digital Healthcare System.
This book experiences the future of patient-centered healthcare and dives into the latest advancements and transformative technologies that are revolutionizing the well-being of individuals around the globe. The readers can join authors on an engaging journey as the authors explore the captivating realm of ambient assisted living and unlock its immense potential for improving healthcare outcomes. This book goes beyond mere exploration; it invites readers to embark on a voyage of discovery as authors unveil the outcomes of groundbreaking research ideas. With a diverse range of applications, from deep learning in healthcare to cutting-edge models, the authors offer a comprehensive view of the opportunities and challenges that lie ahead. Whether you're a healthcare professional, an academic seeking the latest insights, or a researcher delving into the realms of ambient assistive technology, biomedical engineering, or computational intelligence, this book is an invaluable resource. Additionally, postgraduate students pursuing data engineering systems find it to be an essential guide. Each chapter stands independently, providing a comprehensive overview of problem formulation and its tangible outcomes. The readers can immerse themselves in the world of patient-centered healthcare today and become part of the forefront of innovation.
9783031382819
Computational intelligence.
Biomedical engineering.
Artificial intelligence.
Computational Intelligence.
Biomedical Engineering and Bioengineering.
Artificial Intelligence.
Q342
006.3
