Classification In Bioapps
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Classification In Bioapps
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Author : Nilanjan Dey
language : en
Publisher: Springer
Release Date : 2017-11-10
Classification In Bioapps written by Nilanjan Dey and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-10 with Technology & Engineering categories.
This book on classification in biomedical image applications presents original and valuable research work on advances in this field, which covers the taxonomy of both supervised and unsupervised models, standards, algorithms, applications and challenges. Further, the book highlights recent scientific research on artificial neural networks in biomedical applications, addressing the fundamentals of artificial neural networks, support vector machines and other advanced classifiers, as well as their design and optimization. In addition to exploring recent endeavours in the multidisciplinary domain of sensors, the book introduces readers to basic definitions and features, signal filters and processing, biomedical sensors and automation of biomeasurement systems. The target audience includes researchers and students at engineering and medical schools, researchers and engineers in the biomedical industry, medical doctors and healthcare professionals.
Machine Learning In Bio Signal Analysis And Diagnostic Imaging
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Author : Nilanjan Dey
language : en
Publisher: Academic Press
Release Date : 2018-11-30
Machine Learning In Bio Signal Analysis And Diagnostic Imaging written by Nilanjan Dey and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-30 with Science categories.
Machine Learning in Bio-Signal Analysis and Diagnostic Imaging presents original research on the advanced analysis and classification techniques of biomedical signals and images that cover both supervised and unsupervised machine learning models, standards, algorithms, and their applications, along with the difficulties and challenges faced by healthcare professionals in analyzing biomedical signals and diagnostic images. These intelligent recommender systems are designed based on machine learning, soft computing, computer vision, artificial intelligence and data mining techniques. Classification and clustering techniques, such as PCA, SVM, techniques, Naive Bayes, Neural Network, Decision trees, and Association Rule Mining are among the approaches presented. The design of high accuracy decision support systems assists and eases the job of healthcare practitioners and suits a variety of applications. Integrating Machine Learning (ML) technology with human visual psychometrics helps to meet the demands of radiologists in improving the efficiency and quality of diagnosis in dealing with unique and complex diseases in real time by reducing human errors and allowing fast and rigorous analysis. The book's target audience includes professors and students in biomedical engineering and medical schools, researchers and engineers. - Examines a variety of machine learning techniques applied to bio-signal analysis and diagnostic imaging - Discusses various methods of using intelligent systems based on machine learning, soft computing, computer vision, artificial intelligence and data mining - Covers the most recent research on machine learning in imaging analysis and includes applications to a number of domains
Classification Techniques For Medical Image Analysis And Computer Aided Diagnosis
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Author : Nilanjan Dey
language : en
Publisher: Academic Press
Release Date : 2019-07-31
Classification Techniques For Medical Image Analysis And Computer Aided Diagnosis written by Nilanjan Dey and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-31 with Science categories.
Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis covers the most current advances on how to apply classification techniques to a wide variety of clinical applications that are appropriate for researchers and biomedical engineers in the areas of machine learning, deep learning, data analysis, data management and computer-aided diagnosis (CAD) systems design. The book covers several complex image classification problems using pattern recognition methods, including Artificial Neural Networks (ANN), Support Vector Machines (SVM), Bayesian Networks (BN) and deep learning. Further, numerous data mining techniques are discussed, as they have proven to be good classifiers for medical images. - Examines the methodology of classification of medical images that covers the taxonomy of both supervised and unsupervised models, algorithms, applications and challenges - Discusses recent advances in Artificial Neural Networks, machine learning, and deep learning in clinical applications - Introduces several techniques for medical image processing and analysis for CAD systems design
Intelligent Decision Support Systems
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Author : Surekha Borra
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2019-10-21
Intelligent Decision Support Systems written by Surekha Borra and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-21 with Computers categories.
Intelligent prediction and decision support systems are based on signal processing, computer vision (CV), machine learning (ML), software engineering (SE), knowledge based systems (KBS), data mining, artificial intelligence (AI) and include several systems developed from the study of expert systems (ES), genetic algorithms (GA), artificial neural networks (ANN) and fuzzy-logic systems The use of automatic decision support systems in design and manufacturing industry, healthcare and commercial software development systems has the following benifits: Cost savings in companies, due to employment of expert system technology. Fast decision making, completion of projects in time and development of new products. Improvement in decision making capability and quality. Usage of Knowledge database and Preservation of expertise of individuals Eases complex decision problems. Ex: Diagnosis in Healthcare To address the issues and challenges related to development, implementation and application of automatic and intelligent prediction and decision support systems in domains such as manufacturing, healthcare and software product design, development and optimization, this book aims to collect and publish wide ranges of quality articles such as original research contributions, methodological reviews, survey papers, case studies and/or reports covering intelligent systems, expert prediction systems, evaluation models, decision support systems and Computer Aided Diagnosis (CAD).
Smart Systems Innovations In Computing
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Author : Arun K. Somani
language : en
Publisher: Springer Nature
Release Date : 2021-09-03
Smart Systems Innovations In Computing written by Arun K. Somani and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-03 with Technology & Engineering categories.
This book features original papers from the 3rd International Conference on Smart IoT Systems: Innovations and Computing (SSIC 2021), presenting scientific work related to smart solution concepts. It discusses scientific works related to smart solutions concept in the context of computational collective intelligence consisted of interaction between smart devices for smart environments and interactions. Thanks to the high-quality content and the broad range of the topics covered, the book appeals to researchers pursuing advanced studies.
Empirical Research For Futuristic E Commerce Systems Foundations And Applications
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Author : Bilgaiyan, Saurabh
language : en
Publisher: IGI Global
Release Date : 2022-06-24
Empirical Research For Futuristic E Commerce Systems Foundations And Applications written by Bilgaiyan, Saurabh and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-24 with Business & Economics categories.
Recently, there has been an increase in the number of e-commerce users. This has caused online shopping to become a new and challenging market for e-commerce vendors. Security, inventory management, reliability, and performance of e-commerce websites are a few of the challenges associated with the rising popularity of e-commerce. On a daily basis, millions of e-commerce transactions are taking place. This generates a huge amount of data that can be used to solve the various challenges of e-commerce. Further study on how this data can be used to address these issues is required to propel businesses forward. Empirical Research for Futuristic E-Commerce Systems: Foundations and Applications shares experiences and research outcomes on all aspects of intelligent software solutions such as machine learning, nature-inspired computing, and data science for business-to-consumer (B2C) e-commerce. By looking at the exponential growth of the e-commerce market and its popularity, this book also focuses on the current issues, solutions, and future possibilities in the B2C model of e-commerce. Covering a range of critical topics such as online shopping, supply chain management, and blockchain, this reference work is ideal for academic scientists, data scientists, software developers, business experts, researchers, scholars, practitioners, academicians, instructors, and students.
Deep Learning For Medical Applications With Unique Data
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Author : Deepak Gupta
language : en
Publisher: Academic Press
Release Date : 2022-02-15
Deep Learning For Medical Applications With Unique Data written by Deepak Gupta and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-15 with Science categories.
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 volume discusses not only positive findings, but also negative ones obtained by deep learning techniques, including the use of newly developed deep learning techniques rarely reported in the existing literature. The book excludes research works with ready data sets and includes only unique data use to better understand the state of deep learning in real-world cases, along with the feedback and user experiences from physicians and medical staff for applied deep learning-based solutions. Other applications presented in the book include hybrid solutions with deep learning support, disease diagnosis with deep learning focusing on rare diseases and cancer, patient care and treatment, genomics research, as well as research on robotics and autonomous systems. - Introduces deep learning, demonstrating concepts for a wide variety of medical applications using unique data, excluding research with ready datasets - Encompasses a wide variety of biomedical applications, including unsupervised learning, natural language processing, pattern recognition, image and video processing and disease diagnosis - Provides a robust set of methods that will help readers appropriately and judiciously use the most suitable deep learning techniques for their applications
Recent Trends In Image Processing And Pattern Recognition
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Author : KC Santosh
language : en
Publisher: Springer Nature
Release Date : 2022-05-21
Recent Trends In Image Processing And Pattern Recognition written by KC Santosh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-21 with Computers categories.
This volume constitutes the refereed proceedings of the 4th International Conference on Recent Trends in Image Processing and Pattern Recognition, RTIP2R 2021, held in Msida, Malta, in December 2021. Due to the COVID-19 pandemic the conference was held online. The 19 full papers and 14 short papers presented were carefully reviewed and selected from 84 submissions. The papers are organized in the following topical sections: healthcare: medical imaging and informatics; computer vision and pattern recognition; document analysis and recognition; signal processing and machine learning; satellite imaging and remote sensing.
Advances In Bioinformatics Multimedia And Electronics Circuits And Signals
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Author : Lakhmi C. Jain
language : en
Publisher: Springer Nature
Release Date : 2019-10-30
Advances In Bioinformatics Multimedia And Electronics Circuits And Signals written by Lakhmi C. Jain and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-30 with Technology & Engineering categories.
The book features selected high-quality papers presented in International Conference on Computing, Power and Communication Technologies 2019 (GUCON 2019), organized by Galgotias University, India, in September 2019. Discussing in detail topics related to electronics devices, circuits and systems; signal processing; and bioinformatics, multimedia and machine learning, the papers in this book provide interesting reading for researchers, engineers, and students.
Encyclopedia Of Data Science And Machine Learning
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Author : Wang, John
language : en
Publisher: IGI Global
Release Date : 2023-01-20
Encyclopedia Of Data Science And Machine Learning written by Wang, John and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-20 with Computers categories.
Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.