Biomedical engineering is a rapidly growing interdisciplinary area that is providing solutions to biological and medical problems and improving the healthcare system. It is connected to various applications like protein structure prediction, computer-aided drug design, and computerized medical diagnosis based on image and signal data, which accomplish low-cost, accurate, and reliable solutions for improving healthcare services. With the recent advancements, machine learning (ML) and deep l...

This book is designed to consider the recent advancements in hospitals to diagnose various diseases accurately using AI-supported detection procedures. This work examines recent AI-supported disease detection techniques from prominent researchers and clinicians working in the medical imaging processing domain. Within this book, the integration of various AI methods, such as soft computing, machine learning, deep learning, and other related works will be presented. Real clinical images util...

Biomedical and Health Informatics is an important field that brings tremendous opportunities and helps address challenges due to an abundance of available biomedical data. This book examines and demonstrates state-of-the-art approaches for IoT and Machine Learning based biomedical and health related applications. This book aims to provide computational methods for accumulating, updating and changing knowledge in intelligent systems and particularly learning mechanisms that help us to induc...

The Second International Conference on Applied Data Science and Smart Systems (ADSSS-2023) was held on 15-16 December 2023 at Chitkara University, Punjab, India. This multidisciplinary conference focussed on innovation and progressive practices in science, technology, and management. The conference successfully brought together researchers, academicians, and practitioners across different domains such as artificial intelligence and machine learning, software engineering, automation, data s...

Deep Learning for Medical Applications with Unique Data informs readers about the most recent deep learning-based medical applications in which only unique data gathered in real cases are used. The book provides examples of how deep learning can be used in different problem areas and frameworks in both clinical and research settings, including medical image analysis, medical image registration, time series analysis, medical data synthesis, drug discovery, and pre-processing operations. The...

This book includes selected papers from the 4th International Conference on Computational Vision and Bio Inspired Computing (ICCVBIC 2020), held in Coimbatore, India, from November 19 to 20, 2020. This proceedings book presents state-of-the-art research innovations in computational vision and bio-inspired techniques. The book reveals the theoretical and practical aspects of bio-inspired computing techniques, like machine learning, sensor-based models, evolutionary optimization and big data...

Artificial Intelligence in Pathology: Principles and Applications provides a strong foundation of core artificial intelligence principles and their applications in the field of digital pathology. This is a reference of current and emerging use of AI in digital pathology as well as the emerging utility of quantum artificial intelligence and neuromorphic computing in digital pathology. It is a must-have educational resource for lay public, researchers, academicians, practitioners, policymake...

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 t...

This book is a detailed reference on biomedical applications using Deep Learning. Because Deep Learning is an important actor shaping the future of Artificial Intelligence, its specific and innovative solutions for both medical and biomedical are very critical. This book provides a recent view of research works on essential, and advanced topics.The book offers detailed information on the application of Deep Learning for solving biomedical problems. It focuses on different types of ...

The volume explores a wide-range of applications of computer vision in the field of healthcare. Computer vision, an interdisciplinary field that combines image processing, pattern recognition, and artificial intelligence, has the potential to revolutionize healthcare by enabling automated analysis and interpretation of medical images and videos. This chapter will provide an overview of the current advancements and potential future directions of computer vision applications in healthcare. S...

This book offers detailed information on biomedical imaging using Deep Convolutional Neural Networks (Deep CNN). It focuses on different types of biomedical images to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis and image processing perspectives.Deep Learning in Biomedical Signal and Medical Imaging discusses classification, segmentation, detection, tracking, and retrieval applications of non-invasive method...

Mining Biomedical Text, Images and Visual Features for Information Retrieval provides the reader with a broad coverage of the concepts, themes, and instrumentalities of the important and evolving area of biomedical text, images, and visual features towards information retrieval. It aims to encourage an even wider adoption of IR methods for assisting in problem-solving and to stimulate research that may lead to additional innovations in this area of research.The book discusses topics such a...