Breast Cancer Classification Using Machine Learning. An Empirical Study PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Breast Cancer Classification Using Machine Learning. An Empirical Study PDF full book. Access full book title Breast Cancer Classification Using Machine Learning. An Empirical Study by Akor Ugwu. Download full books in PDF and EPUB format.

Breast Cancer Classification Using Machine Learning. An Empirical Study

Breast Cancer Classification Using Machine Learning. An Empirical Study PDF Author: Akor Ugwu
Publisher: GRIN Verlag
ISBN: 334640482X
Category : Medical
Languages : en
Pages : 77

Book Description
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.

Breast Cancer Classification Using Machine Learning. An Empirical Study

Breast Cancer Classification Using Machine Learning. An Empirical Study PDF Author: Akor Ugwu
Publisher: GRIN Verlag
ISBN: 334640482X
Category : Medical
Languages : en
Pages : 77

Book Description
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.

An efficient classification framework for breast cancer using hyper parameter tuned Random Decision Forest Classifier and Bayesian Optimization

An efficient classification framework for breast cancer using hyper parameter tuned Random Decision Forest Classifier and Bayesian Optimization PDF Author: Pratheep Kumar
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 11

Book Description
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

Soft Computing in Data Analytics

Soft Computing in Data Analytics PDF Author: Janmenjoy Nayak
Publisher: Springer
ISBN: 9811305145
Category : Technology & Engineering
Languages : en
Pages : 848

Book Description
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.

C4.5

C4.5 PDF Author: J. Ross Quinlan
Publisher: Morgan Kaufmann
ISBN: 9781558602380
Category : Computers
Languages : en
Pages : 286

Book Description
This book is a complete guide to the C4.5 system as implemented in C for the UNIX environment. It contains a comprehensive guide to the system's use, the source code (about 8,800 lines), and implementation notes.

Discovering Knowledge in Data

Discovering Knowledge in Data PDF Author: Daniel T. Larose
Publisher: John Wiley & Sons
ISBN: 0471687537
Category : Computers
Languages : en
Pages : 240

Book Description
Learn Data Mining by doing data mining Data mining can be revolutionary-but only when it's done right. The powerful black box data mining software now available can produce disastrously misleading results unless applied by a skilled and knowledgeable analyst. Discovering Knowledge in Data: An Introduction to Data Mining provides both the practical experience and the theoretical insight needed to reveal valuable information hidden in large data sets. Employing a "white box" methodology and with real-world case studies, this step-by-step guide walks readers through the various algorithms and statistical structures that underlie the software and presents examples of their operation on actual large data sets. Principal topics include: * Data preprocessing and classification * Exploratory analysis * Decision trees * Neural and Kohonen networks * Hierarchical and k-means clustering * Association rules * Model evaluation techniques Complete with scores of screenshots and diagrams to encourage graphical learning, Discovering Knowledge in Data: An Introduction to Data Mining gives students in Business, Computer Science, and Statistics as well as professionals in the field the power to turn any data warehouse into actionable knowledge. An Instructor's Manual presenting detailed solutions to all the problems in the book is available online.

Breast Imaging

Breast Imaging PDF Author: Christoph I. Lee
Publisher: Oxford University Press
ISBN: 0190270268
Category : Medical
Languages : en
Pages : 545

Book Description
Breast Imaging presents a comprehensive review of the subject matter commonly encountered by practicing radiologists and radiology residents in training. This volume includes succinct overviews of breast cancer epidemiology, screening, staging, and treatment; overviews of all imaging modalities including mammography, tomosynthesis, ultrasound, and MRI; step-by-step approaches for image-guided breast interventions; and high-yield chapters organized by specific imaging finding seen on mammography, tomosynthesis, ultrasound, and MRI. Part of the Rotations in Radiology series, this book offers a guided approach to breast imaging interpretation and techniques, highlighting the nuances necessary to arrive at the best diagnosis and management. Each chapter contains a targeted discussion of an imaging finding which reviews the anatomy and physiology, distinguishing features, imaging techniques, differential diagnosis, clinical issues, key points, and further reading. Breast Imaging is a must-read for residents and practicing radiologists seeking a foundation for the essential knowledge base in breast imaging.

Artificial Intelligence in Medicine

Artificial Intelligence in Medicine PDF Author: David Riaño
Publisher: Springer
ISBN: 303021642X
Category : Computers
Languages : en
Pages : 431

Book Description
This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.

Proceedings of 3rd International Conference on Machine Learning, Advances in Computing, Renewable Energy and Communication

Proceedings of 3rd International Conference on Machine Learning, Advances in Computing, Renewable Energy and Communication PDF Author: Anuradha Tomar
Publisher: Springer Nature
ISBN: 9811928282
Category : Technology & Engineering
Languages : en
Pages : 774

Book Description
This book gathers selected papers presented at International Conference on Machine Learning, Advances in Computing, Renewable Energy and Communication (MARC 2021), held in Krishna Engineering College, Ghaziabad, India, during 10 – 11 December, 2021. This book discusses key concepts, challenges and potential solutions in connection with established and emerging topics in advanced computing, renewable energy and network communications.

Mobile Computing and Sustainable Informatics

Mobile Computing and Sustainable Informatics PDF Author: Subarna Shakya
Publisher: Springer Nature
ISBN: 9811618666
Category : Technology & Engineering
Languages : en
Pages : 875

Book Description
This book gathers selected high-quality research papers presented at International Conference on Mobile Computing and Sustainable Informatics (ICMCSI 2021) organized by Pulchowk Campus, Institute of Engineering, Tribhuvan University, Nepal, during 29–30 January 2021. The book discusses recent developments in mobile communication technologies ranging from mobile edge computing devices, to personalized, embedded and sustainable applications. The book covers vital topics like mobile networks, computing models, algorithms, sustainable models and advanced informatics that supports the symbiosis of mobile computing and sustainable informatics.

Smart Intelligent Computing and Applications

Smart Intelligent Computing and Applications PDF Author: Suresh Chandra Satapathy
Publisher: Springer
ISBN: 9811319219
Category : Technology & Engineering
Languages : en
Pages : 720

Book Description
The proceedings covers advanced and multi-disciplinary research on design of smart computing and informatics. The theme of the book broadly focuses on various innovation paradigms in system knowledge, intelligence and sustainability that may be applied to provide realistic solution to varied problems in society, environment and industries. The volume publishes quality work pertaining to the scope of the conference which is extended towards deployment of emerging computational and knowledge transfer approaches, optimizing solutions in varied disciplines of science, technology and healthcare.