Fuqian Shi – författare

Machine Learning in Bio-Signal Analysis and Diagnostic Imaging presents original research on the advanced analysis and classification techniques of biomedical signals and images that cover both supervised and unsupervised machine learning models, standards, algorithms, and their applications, along with the difficulties and challenges faced by healthcare professionals in analyzing biomedical signals and diagnostic images. These intelligent recommender systems are designed based on machine learning, soft computing, computer vision, artificial intelligence and data mining techniques. Classification and clustering techniques, such as PCA, SVM, techniques, Naive Bayes, Neural Network, Decision trees, and Association Rule Mining are among the approaches presented.

The design of high accuracy decision support systems assists and eases the job of healthcare practitioners and suits a variety of applications. Integrating Machine Learning (ML) technology with human visual psychometrics helps to meet the demands of radiologists in improving the efficiency and quality of diagnosis in dealing with unique and complex diseases in real time by reducing human errors and allowing fast and rigorous analysis. The book's target audience includes professors and students in biomedical engineering and medical schools, researchers and engineers.

Examines a variety of machine learning techniques applied to bio-signal analysis and diagnostic imaging Discusses various methods of using intelligent systems based on machine learning, soft computing, computer vision, artificial intelligence and data mining Covers the most recent research on machine learning in imaging analysis and includes applications to a number of domains

Artificial Intelligence-Driven Metaverse Integration in Smart Healthcare: Advancing Personalized and Predictive Medical Capabilities offers a comprehensive exploration of cutting-edge technologies and their transformative potential in healthcare. The book delves into the application of artificial intelligence (AI) in the healthcare sector, examining machine learning algorithms, natural language processing, and computer vision to enhance healthcare delivery. It also introduces the metaverse, an immersive virtual environment, and explores its integration into medical practices, patient engagement, and health-related experiences. This is an invaluable resource for researchers and practitioners in biomedical fields, health informatics, and personalized and predictive medical systems.In 26 chapters, the book discusses how the convergence of AI and the metaverse contributes to the development of smart healthcare systems that are more efficient, accessible, and personalized. It highlights AI's role in customizing medical treatments, diagnostics, and patient care, leading to more effective healthcare experiences. Additionally, it explores predictive analytics and modeling using AI to prevent diseases, optimize treatments, and improve healthcare outcomes. Providing insights into the current state of AI in healthcare and the potential of metaverse integration, the book includes case studies, practical applications, and future perspectives.Explores the advancement of Artificial Intelligence in healthcare, its prospective for metaverse integration, and its potential to enhance personalized and predictive medical capabilitiesGives insights on how artificial intelligence and the metaverse can be leveraged to provide more personalized healthcare solutionsAddresses the technological hurdles, ethical considerations, and privacy concerns associated with integrating AI and the metaverse into healthcare

These are the proceedings of the International Conference on ISMAC-CVB, held in Palladam, India, in May 2018. The book focuses on research to design new analysis paradigms and computational solutions for quantification of information provided by object recognition, scene understanding of computer vision and different algorithms like convolutional neural networks to allow computers to recognize and detect objects in images with unprecedented accuracy and to even understand the relationships between them.The proceedings treat the convergence of ISMAC in Computational Vision and Bioengineering technology and includes ideas and techniques like 3D sensing, human visual perception, scene understanding, human motion detection and analysis, visualization and graphical data presentation and a very wide range of sensor modalities in terms of surveillance, wearable applications, home automation etc.ISMAC-CVB is a forum for leading academic scientists, researchers and research scholars to exchange and share their experiences and research results about all aspects of computational vision and bioengineering.

This volume gathers selected, peer-reviewed original contributions presented at the International Conference on Computational Vision and Bio-inspired Computing (ICCVBIC) conference which was held in Coimbatore, India, on November 29-30, 2018.

This volume gathers selected, peer-reviewed original contributions presented at the International Conference on Computational Vision and Bio-inspired Computing (ICCVBIC) conference which was held in Coimbatore, India, on November 29-30, 2018.

As machine learning systems prosper, image processing and machine learning techniques will be tightly intertwined and continuously promote each other in real-world settings. Adopting this trend, however, the image processing researchers are faced with few image reconstruction, analysis, and segmentation challenges.

This book includes novel and state-of-the-art research discussions that articulate and report all research aspects, including theoretical and experimental prototypes and applications that incorporate sustainability into emerging applications.

This book includes novel and state-of-the-art research discussions that articulate and report all research aspects, including theoretical and experimental prototypes and applications that incorporate sustainability into emerging applications.

This book features selected papers from the International Conference on Soft Computing for Security Applications (ICSCS 2021), held at Dhirajlal Gandhi College of Technology, Tamil Nadu, India, during June 2021. It covers recent advances in the field of soft computing techniques such as fuzzy logic, neural network, support vector machines, evolutionary computation, machine learning and probabilistic reasoning to solve various real-time challenges. The book presents innovative work by leading academics, researchers, and experts from industry.

This book gathers selected papers presented at the Inventive Communication and Computational Technologies conference (ICICCT 2021), held on 25–26 June 2021 at Gnanamani College of Technology, Tamil Nadu, India.

This book includes selected papers from the 6th International Conference on Computational Vision and Bio Inspired Computing (ICCVBIC 2022), held in Coimbatore, India, from November 18 to 19, 2022. This volume presents state-of-the-art research innovations in computational vision and bio-inspired techniques. It includes theoretical and practical aspects of bio-inspired computing techniques, like machine learning, sensor-based models, evolutionary optimization and big data modeling and management that make use of effectual computing processes in the bio-inspired systems.