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Book
Deep learning for chest radiographs : computer-aided classification
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ISBN: 0323906869 0323901840 9780323906869 9780323901840 Year: 2021 Publisher: London, England : Academic Press,

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Deep Learning for Chest Radiographs enumerates different strategies implemented by the authors for designing an efficient convolution neural network-based computer-aided classification (CAC) system for binary classification of chest radiographs into "Normal" and "Pneumonia." Pneumonia is an infectious disease mostly caused by a bacteria or a virus. The prime targets of this infectious disease are children below the age of 5 and adults above the age of 65, mostly due to their poor immunity and lower rates of recovery. Globally, pneumonia has prevalent footprints and kills more children as compared to any other immunity-based disease, causing up to 15% of child deaths per year, especially in developing countries. Out of all the available imaging modalities, such as computed tomography, radiography or X-ray, magnetic resonance imaging, ultrasound, and so on, chest radiographs are most widely used for differential diagnosis between Normal and Pneumonia. In the CAC system designs implemented in this book, a total of 200 chest radiograph images consisting of 100 Normal images and 100 Pneumonia images have been used. These chest radiographs are augmented using geometric transformations, such as rotation, translation, and flipping, to increase the size of the dataset for efficient training of the Convolutional Neural Networks (CNNs). A total of 12 experiments were conducted for the binary classification of chest radiographs into Normal and Pneumonia. It also includes in-depth implementation strategies of exhaustive experimentation carried out using transfer learning-based approaches with decision fusion, deep feature extraction, feature selection, feature dimensionality reduction, and machine learning-based classifiers for implementation of end-to-end CNN-based CAC system designs, lightweight CNN-based CAC system designs, and hybrid CAC system designs for chest radiographs. This book is a valuable resource for academicians, researchers, clinicians, postgraduate and graduate students in medical imaging, CAC, computer-aided diagnosis, computer science and engineering, electrical and electronics engineering, biomedical engineering, bioinformatics, bioengineering, and professionals from the IT industry. Provides insights into the theory, algorithms, implementation, and application of deep-learning techniques for medical images such as transfer learning using pretrained CNNs, series networks, directed acyclic graph networks, lightweight CNN models, deep feature extraction, and conventional machine learning approaches for feature selection, feature dimensionality reduction, and classification using support vector machine, neuro-fuzzy classifiers Covers the various augmentation techniques that can be used with medical images and the CNN-based CAC system designs for binary classification of medical images focusing on chest radiographs Investigates the development of an optimal CAC system design with deep feature extraction and classification of chest radiographs by comparing the performance of 12 different CAC system designs.

Seventh national conference on artificial intelligence : AAAI 88 : proceedings : August 21-26, 1988, Saint Paul, Minnesota
Authors: --- ---
ISBN: 0929280008 9780929280004 Year: 1988 Publisher: [Etats-Unis] : American association for artificial intelligence,


Book
Human-like machine intelligence
Authors: ---
ISBN: 9780198862536 0198862539 Year: 2021 Publisher: New York : Oxford University Press,

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"In recent years there has been increasing excitement concerning the potential of Artificial Intelligence to transform human society. This book addresses the leading edge of research in this area. The research described aims to address present incompatibilities of Human and Machine reasoning and learning approaches. According to the influential US funding agency DARPA (originator of the Internet and Self-Driving Cars) this new area represents the Third Wave of Artificial Intelligence (3AI, 2020s-2030s), and is being actively investigated in the US, Europe and China. The chapters of this book have been authored by a mixture of UK and other international specialists. Some of the key questions addressed by the Human-Like Computing programme include how AI systems might 1) explain their decisions effectively, 2) interact with human beings in natural language, 3) learn from small numbers of examples and 4) learn with minimal supervision. Solving such fundamental problems involves new foundational research in both the Psychology of perception and interaction as well as the development of novel algorithmic approaches in Artificial Intelligence." [Publisher]


Book
Artificial intelligence in precision health : from concept to applications
Author:
ISBN: 9780128171332 9780128173381 0128173386 0128171332 Year: 2020 Publisher: London : Academic Press,

Computational learning theory. Second european conference, EuroCOLT'95. Barcelona, Spain, March 1995. Proceedings
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ISBN: 3540591192 3540491953 9783540591191 0387591192 9780387591193 Year: 1995 Volume: 904 *99 Publisher: Berlin : Springer-Verlag,

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"This volume presents the proceedings of the Second European Conference on Computational Learning Theory (EuroCOLT '95), held in Barcelona, Spain in March 1995. The book contains full versions of the 28 papers accepted for presentation at the conference as well as three invited papers. All relevant topics in fundamental studies of computational aspects of artificial and natural learning systems and machine learning are covered; in particular artificial and biological neural networks, genetic and evolutionary algorithms, robotics, pattern recognition, inductive logic programming, decision theory, Bayesian/MDL estimation, statistical physics, and cryptography are addressed."--PUBLISHER'S WEBSITE.


Periodical
Journal of Intelligence
ISSN: 20793200 Year: 2012 Publisher: Basel, Switzerland : MDPI AG,

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Keywords

Intellect --- Artificial intelligence --- Cognitive science --- Artificial intelligence. --- Cognitive science. --- Intellect. --- Human intelligence --- Intelligence --- Mind --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- human intelligence --- basis and development of intelligence --- measurement and modeling of intelligence --- structure and processes of intelligence --- emotional and social intelligence --- Ability --- Psychology --- Mental retardation --- Thought and thinking --- Science --- Philosophy of mind --- Bionics --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Artificial Intelligence. --- Computational Intelligence --- AI (Artificial Intelligence) --- Computer Reasoning --- Computer Vision Systems --- Knowledge Acquisition (Computer) --- Knowledge Representation (Computer) --- Machine Intelligence --- Acquisition, Knowledge (Computer) --- Computer Vision System --- Intelligence, Computational --- Intelligence, Machine --- Knowledge Representations (Computer) --- Reasoning, Computer --- Representation, Knowledge (Computer) --- System, Computer Vision --- Systems, Computer Vision --- Vision System, Computer --- Vision Systems, Computer --- Heuristics --- Social sciences

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