Breast Cancer Classification Using Machine Learning An Empirical Study
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Breast Cancer Classification Using Machine Learning An Empirical Study
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Author : Akor Ugwu
language : en
Publisher: GRIN Verlag
Release Date : 2021-05-11
Breast Cancer Classification Using Machine Learning An Empirical Study written by Akor Ugwu and has been published by GRIN Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-11 with Medical categories.
Diploma Thesis from the year 2020 in the subject Medicine - Diagnostics, grade: 3.55, , course: Computer Science, language: English, abstract: The study will classify breast cancers into foremost problems: (Benign tumor and Malignant tumor). A benign tumor is a most cancers does now not invade its surrounding tissue or spread around the host. A malignant tumor is another kind of cancers which can invade its surrounding tissue or spread around the frame of the host. Benign cancers on uncommon event can also surely result in someone’s death, but as a fashionable rule they're no longer nearly as horrific because the malignant cancers. The malignant cancers at the contrary are like those killer bees. In this situation, you do not need to be doing something to them or maybe be everywhere near their hive, they will just spread out and attack you emass – they could even kill the individual if they are extreme enough. Manual manner of cancer category into benign and malignant may be very tedious, susceptible to human error and unnecessarily time consuming. The proposed system while constructed can robotically classify the sort of most cancers into the safe (benign) and also the risky (malignant). This machine plays this role through the usage of machine getting to know algorithm. The following is the extensive of this new system: Classification mistakes could be notably removed, early analysis of disorder, removal of possible human mistakes and the device does no longer die. However, the researcher seeks to detect and assess the class of breast using Machine learning.
Advanced Machine Learning Approaches In Cancer Prognosis
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Author : Janmenjoy Nayak
language : en
Publisher: Springer Nature
Release Date : 2021-05-29
Advanced Machine Learning Approaches In Cancer Prognosis written by Janmenjoy Nayak and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-29 with Technology & Engineering categories.
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.
Automated Breast Cancer Detection And Classification Using Ultrasound Images A Survey
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Author : H.D.Cheng
language : en
Publisher: Infinite Study
Release Date :
Automated Breast Cancer Detection And Classification Using Ultrasound Images A Survey written by H.D.Cheng and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Breast cancer is the second leading cause of death for women all over the world. Since the cause of the disease remains unknown, early detection and diagnosis is the key for breast cancer control, and it can increase the success of treatment, save lives and reduce cost. Ultrasound imaging is one of the most frequently used diagnosis tools to detect and classify abnormalities of the breast.
An Efficient Classification Framework For Breast Cancer Using Hyper Parameter Tuned Random Decision Forest Classifier And Bayesian Optimization
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Author : Pratheep Kumar
language : en
Publisher: Infinite Study
Release Date :
An Efficient Classification Framework For Breast Cancer Using Hyper Parameter Tuned Random Decision Forest Classifier And Bayesian Optimization written by Pratheep Kumar and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with Mathematics categories.
Decision tree algorithm is one of the algorithm which is easily understandable and interpretable algorithm used in both training and application purpose during breast cancer prognosis. To address this problem, Random Decision Forests are proposed. In this manuscript, the breast cancer classification can be determined by combining the advantages of Feature Weight and Hyper Parameter Tuned Random Decision Forest classifier
Artificial Intelligence In Breast Cancer Early Detection And Diagnosis
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Author : Khalid Shaikh
language : en
Publisher: Springer Nature
Release Date : 2020-12-04
Artificial Intelligence In Breast Cancer Early Detection And Diagnosis written by Khalid Shaikh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-04 with Technology & Engineering categories.
This book provides an introduction to next generation smart screening technology for medical image analysis that combines artificial intelligence (AI) techniques with digital screening to develop innovative methods for detecting breast cancer. The authors begin with a discussion of breast cancer, its characteristics and symptoms, and the importance of early screening.They then provide insight on the role of artificial intelligence in global healthcare, screening methods for breast cancer using mammogram, ultrasound, and thermogram images, and the potential benefits of using AI-based systems for clinical screening to more accurately detect, diagnose, and treat breast cancer. Discusses various existing screening methods for breast cancer Presents deep information on artificial intelligence-based screening methods Discusses cancer treatment based on geographical differences and cultural characteristics
Soft Computing In Data Analytics
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Author : Janmenjoy Nayak
language : en
Publisher: Springer
Release Date : 2018-08-21
Soft Computing In Data Analytics written by Janmenjoy Nayak and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-21 with Technology & Engineering categories.
The volume contains original research findings, exchange of ideas and dissemination of innovative, practical development experiences in different fields of soft and advance computing. It provides insights into the International Conference on Soft Computing in Data Analytics (SCDA). It also concentrates on both theory and practices from around the world in all the areas of related disciplines of soft computing. The book provides rapid dissemination of important results in soft computing technologies, a fusion of research in fuzzy logic, evolutionary computations, neural science and neural network systems and chaos theory and chaotic systems, swarm based algorithms, etc. The book aims to cater the postgraduate students and researchers working in the discipline of computer science and engineering along with other engineering branches.
Artificial Intelligence Perspectives And Applications
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Author : Radek Silhavy
language : en
Publisher:
Release Date : 2015
Artificial Intelligence Perspectives And Applications written by Radek Silhavy and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
This volume is based on the research papers presented in the 4th Computer Science On-line Conference. The volume Artificial Intelligence Perspectives and Applications presents new approaches and methods to real-world problems, and in particular, exploratory research that describes novel approaches in the field of artificial intelligence. Particular emphasis is laid on modern trends in selected fields of interest. New algorithms or methods in a variety of fields are also presented. The Computer Science On-line Conference (CSOC 2015) is intended to provide an international forum for discussions on the latest high-quality research results in all areas related to Computer Science. The addressed topics are the theoretical aspects and applications of Computer Science, Artificial Intelligences, Cybernetics, Automation Control Theory and Software Engineering. .
Cancer Prediction For Industrial Iot 4 0
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Author : Meenu Gupta
language : en
Publisher: CRC Press
Release Date : 2021-12-31
Cancer Prediction For Industrial Iot 4 0 written by Meenu Gupta and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-31 with Computers categories.
Cancer Prediction for Industrial IoT 4.0: A Machine Learning Perspective explores various cancers using Artificial Intelligence techniques. It presents the rapid advancement in the existing prediction models by applying Machine Learning techniques. Several applications of Machine Learning in different cancer prediction and treatment options are discussed, including specific ideas, tools and practices most applicable to product/service development and innovation opportunities. The wide variety of topics covered offers readers multiple perspectives on various disciplines. Features • Covers the fundamentals, history, reality and challenges of cancer • Presents concepts and analysis of different cancers in humans • Discusses Machine Learning-based deep learning and data mining concepts in the prediction of cancer • Offers real-world examples of cancer prediction • Reviews strategies and tools used in cancer prediction • Explores the future prospects in cancer prediction and treatment Readers will learn the fundamental concepts and analysis of cancer prediction and treatment, including how to apply emerging technologies such as Machine Learning into practice to tackle challenges in domains/fields of cancer with real-world scenarios. Hands-on chapters contributed by academicians and other professionals from reputed organizations provide and describe frameworks, applications, best practices and case studies on emerging cancer treatment and predictions. This book will be a vital resource to graduate students, data scientists, Machine Learning researchers, medical professionals and analytics managers.
Computational Intelligence And Modelling Techniques For Disease Detection In Mammogram Images
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Author : D. Jude Hemanth
language : en
Publisher: Elsevier
Release Date : 2023-11-16
Computational Intelligence And Modelling Techniques For Disease Detection In Mammogram Images written by D. Jude Hemanth and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-16 with Computers categories.
Computational Intelligence and Modelling Techniques for Disease Detection in Mammogram Images comprehensively examines the wide range of AI-based mammogram analysis methods for medical applications. Beginning with an introductory overview of mammogram data analysis, the book covers the current technologies such as ultrasound, molecular breast imaging (MBI), magnetic resonance (MR), and Positron Emission mammography (PEM), as well as the recent advancements in 3D breast tomosynthesis and 4D mammogram. Deep learning models are presented in each chapter to show how they can assist in the efficient processing of breast images. The book also discusses hybrid intelligence approaches for early-stage detection and the use of machine learning classifiers for cancer detection, staging and density assessment in order to develop a proper treatment plan. This book will not only aid computer scientists and medical practitioners in developing a real-time AI based mammogram analysis system, but also addresses the issues and challenges with the current processing methods which are not conducive for real-time applications. Presents novel ideas for AI based mammogram data analysis Discusses the roles deep learning and machine learning techniques play in efficient processing of mammogram images and in the accurate defining of different types of breast cancer Features dozens of real-world case studies from contributors across the globe
Machine Learning In Cancer Research With Applications In Colon Cancer And Big Data Analysis
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Author : Lu, Zhongyu
language : en
Publisher: IGI Global
Release Date : 2021-05-28
Machine Learning In Cancer Research With Applications In Colon Cancer And Big Data Analysis written by Lu, Zhongyu and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-28 with Medical categories.
Cancer continues to be a growing problem as it is the foremost cause of death worldwide, killing millions of people each year. The number of people battling cancer continues to increase, owing to different reasons, such as lifestyle choices. Clinically, determining the cause of cancer is very challenging and often inaccurate. Incorporating efficient and accurate algorithms to detect cancer cases is becoming increasingly beneficial for scientists in computer science and healthcare, as well as a long-term benefit for doctors, patients, clinic practitioners, and more. Specifically, an automation of computation in machine learning could be a solution in the next generation of big data science technology. Machine Learning in Cancer Research With Applications in Colon Cancer and Big Data Analysis presents algorithms that have been developed to evaluate big data approaches and cancer research. The chapters include artificial intelligence and machine learning approaches, as well as case studies to solve the predictive issues in colon cancer research. This book includes concepts and techniques used to run tasks in an automated manner with the intent to improve better accuracy in comparison with previous studies and methods. This book also covers the processes of research design, development, and outcome analytics in this field. Doctors, IT consultants, IT specialists, medical software professionals, data scientists, researchers, computer scientists, healthcare practitioners, academicians, and students can benefit from this critical resource.