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Advanced computational intelligence paradigms in healthcare 1
This book presents some of the most recent research results on the applications of computational intelligence in healthcare. The contents include: Information model for management of clinical content State-based model for management of type II diabetes Case-based reasoning in medicine Assessing the quality of care in artificial intelligence environment Electronic medical record to examine physician decisions Multi-agent systems for the management of community healthcare Assistive wheelchair navigation Modelling treatment processes using information extraction Neonatal pain detection using face classification techniques Medical education interfaces using virtual patients The book is directed to the computer scientists, medical practitioners, scientists, professors and students of health science, computer science and related disciplines.
Accelerator-Driven System at Kyoto University Critical Assembly
This book is a unique compilation of experimental benchmark analyses of the accelerator-driven system (ADS) at the Kyoto University Critical Assembly (KUCA) on the most recent advances in the development of computational methods.
A vision-based system to early detection of drowning incidents in swimming pools
Being one of the leading causes of death; drowning has become a severe problem in the past few years. Our goal from this project is to focus on the comprehensive survey of drowning detection and prevention techniques. There are various methodologies put up in the domain of swimming pool safety using different intelligent control systems. Various methods have been adopted for drowning detection using the concepts of image processing, pressure and motion sensing. The main objectives of this work are to detect the drowning person in an indoor swimming pool and send an alarm to the lifeguard to rescue if the previously detected person is missing for a specific amount of time.
A Theory of Shape Identification
Recent years have seen dramatic progress in shape recognition algorithms applied to ever-growing image databases. They have been applied to image stitching, stereo vision, image mosaics, solid object recognition and video or web image retrieval. More fundamentally, the ability of humans and animals to detect and recognize shapes is one of the enigmas of perception. The book describes a complete method that starts from a query image and an image database and yields a list of the images in the database containing shapes present in the query image. A false alarm number is associated to each detection. Many experiments will show that familiar simple shapes or images can reliably be identified with false alarm numbers ranging from 10-5 to less than 10-300.
A Pan-Chromatic View of Clusters of Galaxies and the Large-Scale Structure
The reviews presented in this volume cover a wide-range of cluster of galaxies topics like the physics of the ICM gas, the internal cluster dynamics, the detection of clusters using different observational techniques, the great advances in analytical or numerical modeling of clusters, weak and strong lensing effects, the large scale structure as traced by clusters, the cosmological significance of clusters as well as the formation and evolution of clusters within the new cosmological paradigm.
A Century of Ideas : Perspectives from Leading Scientists of the 20th Century
Shortly after its inauguration in 1985 the Birla Science Centre, Hyderabad, India, started a series of lectures by Nobel Laureates and other scientists of international renown, usually in Physics and Astronomy, sometimes in Life Sciences and Chemistry. The present collection mostly consists of lectures on frontier topics. The transcript of each lecture is preceded by a short biography of the Nobel Laureate/Scientist in question.
3D Segmentation for medical images (OsteoVision) = التقطيع ثلاثي الأبعاد للصور الطبية
With the increasing integration of AI across various sectors, artificial intelligence (AI) is already playing a significant role in the healthcare industry, and its use is expected to grow further. AI systems used in image processing and computer vision algorithms have shown a significant ability to perform many operations such as segmentation, classification, and detection. This project presents the application of computer vision algorithms in the field of medical imaging for diagnostic, therapeutic, and interventional purposes. This thesis explores the use of several computer vision algorithms to address different pathologies, specifically brain tumors (glioma) (see Appendix A) and knee osteoarthritis (OA), as well as tracking the progression of knee osteoarthritis using the Kellgren and Lawrence (KL) grading system, a common method for classifying the severity of OA into five grades. To achieve the desired impact, the project employs various techniques, including 3D segmentation for brain tumors, 2D segmentation for knee joints, and multinomial classification for determining the severity of knee OA injuries. The primary aims of the project are to enhance diagnostic accuracy, assist in creating treatment plans, provide an assistive tool for healthcare providers to make more informed decisions, leverage AI's capabilities to detect abnormalities that might escape the human eye, and streamline workflow. To facilitate these goals, the project incorporates a user-friendly UI, a website, and a Flutter-based mobile application, enabling healthcare providers to efficiently integrate these tools into their practice and improve patient care.
3D imaging in endodontics : A new era in diagnosis and treatment
Full understanding of the role of cone beam computed tomography (CBCT) in helping to solve many of the most challenging problems in endodontics. It will shorten the learning curve in application of this exciting imaging technology in a variety of contexts: difficult diagnostic cases, treatment planning, evaluation of internal tooth anatomy prior to root canal therapy, nonsurgical and surgical treatments, early detection and treatment of resorptive defects, and outcomes assessment. The ability to obtain an accurate 3D representation of a tooth and the surrounding structures by means of noninvasive CBCT imaging is changing the approach to clinical decision making in endodontics. Clinicians long accustomed to working in very small, three-dimensional spaces are no longer constrained by the limitations of two-dimensional imaging. The challenges of mastering the new technology can, however, be daunting. The detailed guidance contained in this book will help endodontists to take full advantage of the important benefits offered by CBCT.
3D imaging in endodontics : A new era in diagnosis and treatment
Provides readers with a full understanding of the role of cone beam computed tomography (CBCT) in helping to solve many of the most challenging problems in endodontics. It will shorten the learning curve in application of this exciting imaging technique in a variety of contexts: difficult diagnostic cases, treatment planning, evaluation of internal tooth anatomy prior to root canal therapy, nonsurgical and surgical treatments, early detection and treatment of resorptive defects, and outcomes assessment.
