Artificial Neural Networks In Cancer Diagnosis Prognosis And Patient Management
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Author : R. N. G. Naguib,G. V. Sherbet Publisher : CRC Press Page : 216 pages File Size : 45,8 Mb Release : 2001-06-22 Category : Medical ISBN : 9781420036381
Artificial Neural Networks in Cancer Diagnosis, Prognosis, and Patient Management by R. N. G. Naguib,G. V. Sherbet Pdf
The potential value of artificial neural networks (ANN) as a predictor of malignancy has begun to receive increased recognition. Research and case studies can be found scattered throughout a multitude of journals. Artificial Neural Networks in Cancer Diagnosis, Prognosis, and Patient Management brings together the work of top researchers - primaril
Artificial Intelligence Techniques in Breast Cancer Diagnosis and Prognosis by Ashlesha Jain,Ajita Jain,Sandhya Jain,Lakhmi Jain Pdf
The main aim of this book is to present a sample of recent research on the application of novel artificial intelligence paradigms to the diagnosis and prognosis of breast cancer. These paradigms include neural networks, fuzzy logic and evolutionary computing. Artificial intelligence techniques offer advantages — such as adaptation, fault tolerance, learning and human-like behavior — over conventional computing techniques. The idea is to combine the pathological, intelligent and statistical approaches to enable simple and accurate diagnosis and prognosis. This book is the first of its kind on the topic of artificial intelligence in breast cancer. It presents the applications of artificial intelligence in breast cancer diagnosis and prognosis, and includes state-of-the-art concepts in the field. It contains contributions from Australia, Germany, Italy, UK and the USA. Contents:An Introduction to Breast Cancer Diagnosis, Prognosis, and Artificial Intelligence (N Harbeck et al.)Automatic Image Feature Extraction for Diagnosis and Prognosis of Breast Cancer (M J Bottema et al.)Decision Support in Breast Cancer: Recent Advances in Prognostic and Predictive Techniques (R Kates et al.)MammoNet: A Bayesian Network Diagnosing Breast Cancer (L M Roberts)Predicting Prognosis and Treatment Response in Breast Cancer Patients (M G Daidone & D Coradini)Computer-Aided Breast Cancer Diagnosis (H-P Chan et al.)Which Decision Support Technologies are Appropriate for the Cytodiagnosis of Breast Cancer? (S S Cross et al.)Xcyt: A System for Remote Cytological Diagnosis and Prognosis of Breast Cancer (W N Street) Readership: Medical practitioners, researchers and graduate students. Keywords:Artificial Intelligence;Soft Computing;Breast Cancer;Diagnosis;Prognosis;Fuzzy Systems;Neural NetworksReviews:“The editors have done an excellent job of putting together a book that highlights the advances and controversies that surround the subject … The book will be of particular interest to clinical decision support systems designers and academic oncologists.”Cancer Forum
Advanced Machine Learning Approaches in Cancer Prognosis by Janmenjoy Nayak,Margarita N. Favorskaya,Seema Jain,Bighnaraj Naik,Manohar Mishra Pdf
This book introduces a variety of advanced machine learning approaches covering the areas of neural networks, fuzzy logic, and hybrid intelligent systems for the determination and diagnosis of cancer. Moreover, the tactical solutions of machine learning have proved its vast range of significance and, provided novel solutions in the medical field for the diagnosis of disease. This book also explores the distinct deep learning approaches that are capable of yielding more accurate outcomes for the diagnosis of cancer. In addition to providing an overview of the emerging machine and deep learning approaches, it also enlightens an insight on how to evaluate the efficiency and appropriateness of such techniques and analysis of cancer data used in the cancer diagnosis. Therefore, this book focuses on the recent advancements in the machine learning and deep learning approaches used in the diagnosis of different types of cancer along with their research challenges and future directions for the targeted audience including scientists, experts, Ph.D. students, postdocs, and anyone interested in the subjects discussed.
Author : R. N. G. Naguib,G. V. Sherbet Publisher : CRC Press Page : 192 pages File Size : 49,6 Mb Release : 2001-06-22 Category : Medical ISBN : 9781000654059
Artificial Neural Networks in Cancer Diagnosis, Prognosis, and Patient Management by R. N. G. Naguib,G. V. Sherbet Pdf
The potential value of artificial neural networks (ANN) as a predictor of malignancy has begun to receive increased recognition. Research and case studies can be found scattered throughout a multitude of journals. Artificial Neural Networks in Cancer Diagnosis, Prognosis, and Patient Management brings together the work of top researchers - primaril
Computational Intelligence in Oncology by Khalid Raza Pdf
This book encapsulates recent applications of CI methods in the field of computational oncology, especially cancer diagnosis, prognosis, and its optimized therapeutics. The cancer has been known as a heterogeneous disease categorized in several different subtypes. According to WHO’s recent report, cancer is a leading cause of death worldwide, accounting for over 10 million deaths in the year 2020. Therefore, its early diagnosis, prognosis, and classification to a subtype have become necessary as it facilitates the subsequent clinical management and therapeutics plan. Computational intelligence (CI) methods, including artificial neural networks (ANNs), fuzzy logic, evolutionary computations, various machine learning and deep learning, and nature-inspired algorithms, have been widely utilized in various aspects of oncology research, viz. diagnosis, prognosis, therapeutics, and optimized clinical management. Appreciable progress has been made toward the understanding the hallmarks of cancer development, progression, and its effective therapeutics. However, notwithstanding the extrinsic and intrinsic factors which lead to drastic increment in incidence cases, the detection, diagnosis, prognosis, and therapeutics remain an apex challenge for the medical fraternity. With the advent in CI-based approaches, including nature-inspired techniques, and availability of clinical data from various high-throughput experiments, medical consultants, researchers, and oncologists have seen a hope to devise and employ CI in various aspects of oncology. The main aim of the book is to occupy state-of-the-art applications of CI methods which have been derived from core computer sciences to back medical oncology. This edited book covers artificial neural networks, fuzzy logic and fuzzy inference systems, evolutionary algorithms, various nature-inspired algorithms, and hybrid intelligent systems which are widely appreciated for the diagnosis, prognosis, and optimization of therapeutics of various cancers. Besides, this book also covers multi-omics exploration, gene expression analysis, gene signature identification of cancers, genomic characterization of tumors, anti-cancer drug design and discovery, drug response prediction by means of CI, and applications of IoT, IoMT, and blockchain technology in cancer research.
Medical Diagnosis Using Artificial Neural Networks by Moein, Sara Pdf
Advanced conceptual modeling techniques serve as a powerful tool for those in the medical field by increasing the accuracy and efficiency of the diagnostic process. The application of artificial intelligence assists medical professionals to analyze and comprehend a broad range of medical data, thus eliminating the potential for human error. Medical Diagnosis Using Artificial Neural Networks introduces effective parameters for improving the performance and application of machine learning and pattern recognition techniques to facilitate medical processes. This book is an essential reference work for academicians, professionals, researchers, and students interested in the relationship between artificial intelligence and medical science through the use of informatics to improve the quality of medical care.
Deep Learning for Cancer Diagnosis by Utku Kose,Jafar Alzubi Pdf
This book explores various applications of deep learning to the diagnosis of cancer,while also outlining the future face of deep learning-assisted cancer diagnostics. As is commonly known, artificial intelligence has paved the way for countless new solutions in the field of medicine. In this context, deep learning is a recent and remarkable sub-field, which can effectively cope with huge amounts of data and deliver more accurate results. As a vital research area, medical diagnosis is among those in which deep learning-oriented solutions are often employed. Accordingly, the objective of this book is to highlight recent advanced applications of deep learning for diagnosing different types of cancer. The target audience includes scientists, experts, MSc and PhD students, postdocs, and anyone interested in the subjects discussed. The book can be used as a reference work to support courses on artificial intelligence, medical and biomedicaleducation.
Outcome Prediction in Cancer by Azzam F.G. Taktak,Anthony C. Fisher Pdf
This book is organized into 4 sections, each looking at the question of outcome prediction in cancer from a different angle. The first section describes the clinical problem and some of the predicaments that clinicians face in dealing with cancer. Amongst issues discussed in this section are the TNM staging, accepted methods for survival analysis and competing risks. The second section describes the biological and genetic markers and the rôle of bioinformatics. Understanding of the genetic and environmental basis of cancers will help in identifying high-risk populations and developing effective prevention and early detection strategies. The third section provides technical details of mathematical analysis behind survival prediction backed up by examples from various types of cancers. The fourth section describes a number of machine learning methods which have been applied to decision support in cancer. The final section describes how information is shared within the scientific and medical communities and with the general population using information technology and the World Wide Web. * Applications cover 8 types of cancer including brain, eye, mouth, head and neck, breast, lungs, colon and prostate * Include contributions from authors in 5 different disciplines * Provides a valuable educational tool for medical informatics
Handbook of Immunohistochemistry and in situ Hybridization of Human Carcinomas by M. A. Hayat Pdf
Immunohistochemistry is the use of specific antibodies to stain particular molecular species in situ. This technique has allowed the identification of many more cell types than could be visualized by classical histology, particularly in the immune system and among the scattered hormone-secreting cells of the endocrine system, and has the potential to improve diagnosis, prognosis and therapeutic options of cancer. This book discusses all aspects of immunohistochemistry and in situ hybridization technologies and the important role they play in reaching a cancer diagnosis. It provides step-by-step instructions on the methods of additional molecular technologies such as DNA microarrays, and microdissection, along with the benefits and limitations of each method. The topics of region-specific gene expression, its role in cancer development and the techniques that assist in the understanding of the molecular basis of disease are relevant and necessary in science today. * The only book available that translates molecular genetics into cancer diagnosis * The results of each Immunohistochemical and in situ hybridization method are presented in the form of color illustrations * Methods discussed were either developed or refined by expert contributors in their own laboratories
Information Systems Architecture and Technology: Proceedings of 40th Anniversary International Conference on Information Systems Architecture and Technology – ISAT 2019 by Zofia Wilimowska,Leszek Borzemski,Jerzy Świątek Pdf
This three-volume book highlights significant advances in the development of new information systems technologies and architectures. Further, it helps readers solve specific research and analytical problems and glean useful knowledge and business value from data. Each chapter provides an analysis of a specific technical problem, followed by a numerical analysis, simulation, and implementation of the solution to the real-world problem. Managing an organization, especially in today’s rapidly changing environment, is a highly complex process. Increased competition in the marketplace, especially as a result of the massive and successful entry of foreign businesses into domestic markets, changes in consumer behaviour, and broader access to new technologies and information, calls for organisational restructuring and the introduction and modification of management methods using the latest scientific advances. This situation has prompted various decision-making bodies to introduce computer modelling of organization management systems. This book presents the peer-reviewed proceedings of the 40th Anniversary International Conference “Information Systems Architecture and Technology” (ISAT), held on September 15–17, 2019, in Wrocław, Poland. The conference was organised by the Computer Science Department, Faculty of Computer Science and Management, Wroclaw University of Sciences and Technology, and University of Applied Sciences in Nysa, Poland. The papers have been grouped into three major sections: Part I—discusses topics including, but not limited to, artificial intelligence methods, knowledge discovery and data mining, big data, knowledge-based management, Internet of Things, cloud computing and high-performance computing, distributed computer systems, content delivery networks, and service-oriented computing. Part II—addresses various topics, such as system modelling for control, recognition and decision support, mathematical modelling in computer system design, service-oriented systems, and cloud computing, and complex process modelling. Part III—focuses on a number of themes, like knowledge-based management, modelling of financial and investment decisions, modelling of managerial decisions, production systems management, and maintenance, risk management, small business management, and theories and models of innovation.
Applied Smart Health Care Informatics by Sourav De,Rik Das,Siddhartha Bhattacharyya,Ujjwal Maulik Pdf
Applied Smart Health Care Informatics Explores how intelligent systems offer new opportunities for optimizing the acquisition, storage, retrieval, and use of information in healthcare Applied Smart Health Care Informatics explores how health information technology and intelligent systems can be integrated and deployed to enhance healthcare management. Edited and authored by leading experts in the field, this timely volume introduces modern approaches for managing existing data in the healthcare sector by utilizing artificial intelligence (AI), meta-heuristic algorithms, deep learning, the Internet of Things (IoT), and other smart technologies. Detailed chapters review advances in areas including machine learning, computer vision, and soft computing techniques, and discuss various applications of healthcare management systems such as medical imaging, electronic medical records (EMR), and drug development assistance. Throughout the text, the authors propose new research directions and highlight the smart technologies that are central to establishing proactive health management, supporting enhanced coordination of care, and improving the overall quality of healthcare services. Provides an overview of different deep learning applications for intelligent healthcare informatics management Describes novel methodologies and emerging trends in artificial intelligence and computational intelligence and their relevance to health information engineering and management Proposes IoT solutions that disseminate essential medical information for intelligent healthcare management Discusses mobile-based healthcare management, content-based image retrieval, and computer-aided diagnosis using machine and deep learning techniques Examines the use of exploratory data analysis in intelligent healthcare informatics systems Applied Smart Health Care Informatics: A Computational Intelligence Perspective is an invaluable text for graduate students, postdoctoral researchers, academic lecturers, and industry professionals working in the area of healthcare and intelligent soft computing.
Clinical Technologies: Concepts, Methodologies, Tools and Applications by Management Association, Information Resources Pdf
"This multi-volume book delves into the many applications of information technology ranging from digitizing patient records to high-performance computing, to medical imaging and diagnostic technologies, and much more"--
Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery: Implications in Business, Science, and Engineering by Chiong, Raymond Pdf
Recently, nature has stimulated many successful techniques, algorithms, and computational applications allowing conventionally difficult problems to be solved through novel computing systems. Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery: Implications in Business, Science, and Engineering provides the latest findings in nature-inspired algorithms and their applications for breakthroughs in a wide range of disciplinary fields. This defining reference collection contains chapters written by leading researchers and well-known academicians within the field, offering readers a valuable and enriched accumulation of knowledge.
Perspectives of Knowledge Management in Urban Health by Michael Christopher Gibbons,Rajeev Bali,Nilmini Wickramasinghe Pdf
It is a tragic paradox of American health care: a system renowned for world-class doctors, the latest medical technologies, and miraculous treatments has shocking inadequacies when it comes to the health of the urban poor. Urban Health Knowledge Management outlines bold, workable strategies for addressing this disparity and eliminating the “knowledge islands” that so often disrupt effective service delivery. The book offers a wide-reaching global framework for organizational competence leading to improved care quality and outcomes for traditionally underserved clients in diverse, challenging settings. Its contributors understand the issues fluently, imparting both macro and micro concepts of KM with clear rationales and real-world examples as they: • Analyze key aspects of KM and explains their applicability to urban health. • Introduce the KM tools and technologies most relevant to health care delivery. • Offer evidence of the role of KM in improving clinical efficacy and executive decision-making. • Provide extended case examples of KM-based programs used in Washington, D.C. (child health), South Africa (HIV/AIDS), and Australia (health inequities). • Apply KM principles to urban health needs in developing countries. • Discuss new approaches to managing, evaluating, and improving delivery systems in the book’s “Measures and Metrics” section. Urban health professionals, as well as health care executives and administrators, will find Urban Health Knowledge Management a significant resource for bringing service delivery up to speed at a time of great advancement and change.
First published in 1943, VITAMINS AND HORMONES is the longest-running serial published by Academic Press. In the early days of the Serial, the subjects of vitamins and hormones were quite distinct. The Editorial Board now reflects expertise in the field of hormone action, vitamin action, X-ray crystal structure, physiology, and enzyme mechanisms. Under the capable and qualified editorial leadership of Dr. Gerald Litwack, VITAMINS AND HORMONES continues to publish cutting-edge reviews of interest to endocrinologists, biochemists, nutritionists, pharmacologists, cell biologists, and molecular biologists. Others interested in the structure and function of biologically active molecules like hormones and vitamins will, as always, turn to this series for comprehensive reviews by leading contributors to this and related disciplines. *Includes color illustrations *Available on ScienceDirect *Longest running series published by Academic Press *Contributions by leading international authorities
