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Author: Nilufer Bulut
Publisher: BoD – Books on Demand
ISBN: 1789235669
Category : Medical
Languages : en
Pages : 228
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Book Description
The book 'Breast Cancer and Surgery' summarizes the treatment options from the onset of breast carcinogenesis to early-local advanced and metastatic breast cancer. Chemotherapy alternatives, drug resistance and local and surgical treatment preferences are extensively discussed and this information is especially directed at clinicians, researchers, and students. This book includes a comparison between different chemotherapy agents and targeted therapies with published phase II-III studies. The importance of palliative care and dietary supplements administered during the treatment course in reducing the comorbidity of patients is emphasized. Photodynamic treatments have been included in this book. A comprehensive and up-to-date information exchange that can be accessed through a single source is provided to all researchers interested in breast cancer.
Author: Nilufer Bulut
Publisher: BoD – Books on Demand
ISBN: 1789235669
Category : Medical
Languages : en
Pages : 228
Get Book Here
Book Description
The book 'Breast Cancer and Surgery' summarizes the treatment options from the onset of breast carcinogenesis to early-local advanced and metastatic breast cancer. Chemotherapy alternatives, drug resistance and local and surgical treatment preferences are extensively discussed and this information is especially directed at clinicians, researchers, and students. This book includes a comparison between different chemotherapy agents and targeted therapies with published phase II-III studies. The importance of palliative care and dietary supplements administered during the treatment course in reducing the comorbidity of patients is emphasized. Photodynamic treatments have been included in this book. A comprehensive and up-to-date information exchange that can be accessed through a single source is provided to all researchers interested in breast cancer.
Author: Shahnorbanun Sahran
Publisher:
ISBN:
Category : Medicine
Languages : en
Pages :
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Book Description
This chapter discusses radio-pathological correlation with recent imaging advances such as machine learning (ML) with the use of technical methods such as mammography and histopathology. Although criteria for diagnostic categories for radiology and pathology are well established, manual detection and grading, respectively, are tedious and subjective processes and thus suffer from inter-observer and intra-observer variations. Two most popular techniques that use ML, computer aided detection (CADe) and computer aided diagnosis (CADx), are presented. CADe is a rejection model based on SVM algorithm which is used to reduce the False Positive (FP) of the output of the Chan-Vese segmentation algorithm that was initialized by the marker controller watershed (MCWS) algorithm. CADx method applies the ensemble framework, consisting of four-base SVM (RBF) classifiers, where each base classifier is a specialist and is trained to use the selected features of a particular tissue component. In general, both proposed methods offer alternative decision-making ability and are able to assist the medical expert in giving second opinion on more precise nodule detection. Hence, it reduces FP rate that causes over segmentation and improves the performance for detection and diagnosis of the breast cancer and is able to create a platform that integrates diagnostic reporting system.
Author: Khalid Shaikh
Publisher: Springer Nature
ISBN: 3030592081
Category : Technology & Engineering
Languages : en
Pages : 107
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Book Description
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
Author: Janmenjoy Nayak
Publisher: Springer Nature
ISBN: 3030719758
Category : Technology & Engineering
Languages : en
Pages : 461
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Book Description
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.
Author: Mia Kathleen Markey
Publisher:
ISBN:
Category : Breast
Languages : en
Pages : 368
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Book Description
Author: Christoph I. Lee
Publisher: Oxford University Press
ISBN: 0190270268
Category : Medical
Languages : en
Pages : 545
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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.
Author: Akor Ugwu
Publisher: GRIN Verlag
ISBN: 334640482X
Category : Medical
Languages : en
Pages : 77
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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.
Author: Sathiyamoorthi Velayutham
Publisher: IGI Global, Engineering Science Reference
ISBN: 9781522599029
Category : Machine learning
Languages : en
Pages : 0
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Book Description
"This book examines the practical applications and implementation of various machine learning techniques in various fields such as agriculture, medical, image processing, and networking"--
Author: DR. SYED HAUIDER ABBAS
Publisher: Blue Hill Publications
ISBN: 9358298685
Category : Antiques & Collectibles
Languages : en
Pages : 79
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Book Description
First and foremost, we express our deepest gratitude to God. Throughout the process of compiling this book, we have come to appreciate the profound impact of the gift of writing, which has empowered us to pursue our dreams and believe in our passions. Without divine trust and guidance, this accomplishment would not have been possible. We extend our sincere thanks to all those involved in this project, especially the authors and reviewers whose contributions were instrumental in bringing this book to fruition. Their support has been invaluable, and we are grateful for their dedication and expertise. We also thank God for granting us the opportunity to delve into this highly relevant subject matter at this time, and we acknowledge the collective efforts of each author for their invaluable contributions. Special appreciation goes to all the chapter authors who generously shared their time and expertise. Additionally, we acknowledge the valuable feedback provided by the peer reviewers, whose suggestions greatly enhanced the quality, coherence, and content of the chapters. We are especially grateful to those authors who served as referees, dedicating their time and effort to ensure the integrity of this work. DR. SYED HAUIDER ABBAS DR. KRISHNA PRASAD K
Author: Amit Kumar Tyagi
Publisher: John Wiley & Sons
ISBN: 1119785723
Category : Computers
Languages : en
Pages : 532
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Book Description
The book details deep learning models like ANN, RNN, LSTM, in many industrial sectors such as transportation, healthcare, military, agriculture, with valid and effective results, which will help researchers find solutions to their deep learning research problems. We have entered the era of smart world devices, where robots or machines are being used in most applications to solve real-world problems. These smart machines/devices reduce the burden on doctors, which in turn make their lives easier and the lives of their patients better, thereby increasing patient longevity, which is the ultimate goal of computer vision. Therefore, the goal in writing this book is to attempt to provide complete information on reliable deep learning models required for e-healthcare applications. Ways in which deep learning can enhance healthcare images or text data for making useful decisions are discussed. Also presented are reliable deep learning models, such as neural networks, convolutional neural networks, backpropagation, and recurrent neural networks, which are increasingly being used in medical image processing, including for colorization of black and white X-ray images, automatic machine translation images, object classification in photographs/images (CT scans), character or useful generation (ECG), image caption generation, etc. Hence, reliable deep learning methods for the perception or production of better results are a necessity for highly effective e-healthcare applications. Currently, the most difficult data-related problem that needs to be solved concerns the rapid increase of data occurring each day via billions of smart devices. To address the growing amount of data in healthcare applications, challenges such as not having standard tools, efficient algorithms, and a sufficient number of skilled data scientists need to be overcome. Hence, there is growing interest in investigating deep learning models and their use in e-healthcare applications. Audience Researchers in artificial intelligence, big data, computer science, and electronic engineering, as well as industry engineers in transportation, healthcare, biomedicine, military, agriculture.
