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Artificial Neural Networks in Cancer Diagnosis, Prognosis, and Patient Management

why neural networks are more accurate. Artificial Neural Networks in Cancer Diagnosis, Prognosis, and Patient Management gives you an;

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Artificial Neural Networks

This volume presents examples of how Artificial Neural Networks (ANNs) are applied in biological sciences and related areas. Chapters cover;

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New Developments in Computer Networks

diagnosis in a distillation column by MLP neural networks and generic architecture for artificial neural networks.;

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Advanced Machine Learning Approaches in Cancer Prognosis

intelligent systems for the determination and diagnosis of cancer. Moreover, the tactical solutions of machine learning have proved its vast range;

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New Developments In Artificial Neural Networks Research

in chromatography and spectroscopy; heterogeneous neural networks and tuning differential evolution for artificial neural networks.;

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Gastric Cancer

, and PET/CT in the diagnosis, staging and follow-up of patients with gastric cancer is emphasized. The relative strengths and limitations;

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Deep Neural Networks and Applications

management. It further elaborates on the artificial neural networks in detail and discusses the practical applications of the deep neutral networks;

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Precision Cancer Medicine

artificial intelligence technology in cancer diagnosis and management. It is also relevant to oncologists and medical practitioners involved;

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Focus on Artificial Neural Networks

artificial neural networks in environmental sciences and chemical engineering; application of artificial neural networks in the development;

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Application of Signal Processing Tools and Artificial Neural Network in Diagnosis of Power System Faults

systems. Application of Signal Processing Tools and Neural Network in Diagnosis of Power System Faults examines power system faults and;

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Recent Progress in Artificial Neural Networks

Artificial neural networks (ANNs) are computing systems that are motivated by the design and functioning of biological neural networks. Its;

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Advanced Neural Network-Based Computational Schemes for Robust Fault Diagnosis

The present book is devoted to problems of adaptation of artificial neural networks to robust fault diagnosis schemes. It presents neural;

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Neural Networks for Complete Beginners

learn the relationship between the neurons which make up the human brain and the artificial neurons. Artificial neural networks embrace the;

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Artificial Neural Networks

-layered learning network based on simple math rules. The structure of an artificial neural network consists of an input layer, an output layer and;

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Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis

of machine learning, deep learning, data analysis, data management and computer-aided diagnosis (CAD) systems design. The book covers several complex;

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Principles Of Artificial Neural Networks

The field of Artificial Neural Networks is the fastest growing field in Information Technology and specifically, in Artificial Intelligence;

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State of the Art in Neural Networks and Their Applications

State of the Art in Neural Networks and Their Applications presents the latest advances in artificial neural networks and their;

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Advances in Surgical Pathology

essential histopathology of gastric cancer as well as related topics such as imaging evaluation, molecular diagnosis, and personalized treatment;

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Non-Invasive Technologies for the Diagnosis and Management of Skin Cancer, An Issue of Dermatologic Clinics

the Diagnosis of Skin Cancer. Articles in this issue include: Current state and issues of clinical inspection; Tele-dermatology applications;

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Male Breast Cancer

, the evidence-based management of these cases is reviewed. Male Breast Cancer concludes with a discussion on determining prognosis and the;

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Neural Networks

explored in differentiating breast cancers with artificial neural networks, one example of computer-aided diagnosis systems. The authors aim to;

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Designs and Applied Principles of Artificial Neural Networks

This book presents a broad overview on the current various design modules and applications of artificial neural systems. Artificial neural;

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Management of Thyroid Nodules and Differentiated Thyroid Cancer

controversies in the management of indeterminate thyroid nodules and cancer, and reviews the latest data on use of molecular testing for diagnosis and;

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Evolutionary Machine Learning Techniques

. The book also covers applications of the improved artificial neural networks to solve classification, clustering, prediction and regression;

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Evolutionary Machine Learning Techniques

machines, evolutionary feature selection, artificial neural networks including feed-forward neural networks, multi-layer perceptron, probabilistic;

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Cancer Neurology in Clinical Practice

that cancer patients experience, and show how they should be interpreted and evaluated. Organized by both symptom and organ, the book carefully;

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Artificial Intelligence in Medicine

is organized in topical sections on medical records, temporal reasoning and simulation, probabilistic models, patient management and therapy planning;

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