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The Use Of Deep Learning In Mapping And Diagnosis Of Cancers
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Book Synopsis The use of deep learning in mapping and diagnosis of cancers by : Fu Wang
Download or read book The use of deep learning in mapping and diagnosis of cancers written by Fu Wang and published by Frontiers Media SA. This book was released on 2023-01-18 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Deep Learning for Cancer Diagnosis by : Utku Kose
Download or read book Deep Learning for Cancer Diagnosis written by Utku Kose and published by Springer Nature. This book was released on 2020-09-12 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores various applications of deep learning to the diagnosis of cancer,while also outlining the future face of deep learning-assisted cancer diagnostics. As is commonly known, artificial intelligence has paved the way for countless new solutions in the field of medicine. In this context, deep learning is a recent and remarkable sub-field, which can effectively cope with huge amounts of data and deliver more accurate results. As a vital research area, medical diagnosis is among those in which deep learning-oriented solutions are often employed. Accordingly, the objective of this book is to highlight recent advanced applications of deep learning for diagnosing different types of cancer. The target audience includes scientists, experts, MSc and PhD students, postdocs, and anyone interested in the subjects discussed. The book can be used as a reference work to support courses on artificial intelligence, medical and biomedicaleducation.
Book Synopsis Deep Learning in Cancer Diagnostics by : Mohd Hafiz Arzmi
Download or read book Deep Learning in Cancer Diagnostics written by Mohd Hafiz Arzmi and published by Springer Nature. This book was released on 2023-01-18 with total page 41 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cancer is the leading cause of mortality in most, if not all, countries around the globe. It is worth noting that the World Health Organisation (WHO) in 2019 estimated that cancer is the primary or secondary leading cause of death in 112 of 183 countries for individuals less than 70 years old, which is alarming. In addition, cancer affects socioeconomic development as well. The diagnostics of cancer are often carried out by medical experts through medical imaging; nevertheless, it is not without misdiagnosis owing to a myriad of reasons. With the advancement of technology and computing power, the use of state-of-the-art computational methods for the accurate diagnosis of cancer is no longer far-fetched. In this brief, the diagnosis of four types of common cancers, i.e., breast, lung, oral and skin, are evaluated with different state-of-the-art feature-based transfer learning models. It is expected that the findings in this book are insightful to various stakeholders in the diagnosis of cancer.
Book Synopsis Current Applications of Deep Learning in Cancer Diagnostics by : Jyotismita Chaki
Download or read book Current Applications of Deep Learning in Cancer Diagnostics written by Jyotismita Chaki and published by CRC Press. This book was released on 2023-02-22 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines deep learning-based approaches in the field of cancer diagnostics, as well as pre-processing techniques, which are essential to cancer diagnostics. Topics include introduction to current applications of deep learning in cancer diagnostics, pre-processing of cancer data using deep learning, review of deep learning techniques in oncology, overview of advanced deep learning techniques in cancer diagnostics, prediction of cancer susceptibility using deep learning techniques, prediction of cancer reoccurrence using deep learning techniques, deep learning techniques to predict the grading of human cancer, different human cancer detection using deep learning techniques, prediction of cancer survival using deep learning techniques, complexity in the use of deep learning in cancer diagnostics, and challenges and future scopes of deep learning techniques in oncology.
Book Synopsis Advanced Machine Learning Approaches in Cancer Prognosis by : Janmenjoy Nayak
Download or read book Advanced Machine Learning Approaches in Cancer Prognosis written by Janmenjoy Nayak and published by Springer Nature. This book was released on 2021-05-29 with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Machine and Deep Learning in Oncology, Medical Physics and Radiology by : Issam El Naqa
Download or read book Machine and Deep Learning in Oncology, Medical Physics and Radiology written by Issam El Naqa and published by Springer Nature. This book was released on 2022-02-02 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book, now in an extensively revised and updated second edition, provides a comprehensive overview of both machine learning and deep learning and their role in oncology, medical physics, and radiology. Readers will find thorough coverage of basic theory, methods, and demonstrative applications in these fields. An introductory section explains machine and deep learning, reviews learning methods, discusses performance evaluation, and examines software tools and data protection. Detailed individual sections are then devoted to the use of machine and deep learning for medical image analysis, treatment planning and delivery, and outcomes modeling and decision support. Resources for varying applications are provided in each chapter, and software code is embedded as appropriate for illustrative purposes. The book will be invaluable for students and residents in medical physics, radiology, and oncology and will also appeal to more experienced practitioners and researchers and members of applied machine learning communities.
Book Synopsis Application of Deep Learning Methods in Healthcare and Medical Science by : Rohit Tanwar
Download or read book Application of Deep Learning Methods in Healthcare and Medical Science written by Rohit Tanwar and published by CRC Press. This book was released on 2023-01-12 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: The volume provides a wealth of up-to-date information on developments and applications of deep learning in healthcare and medicine, providing deep insight and understanding of novel applications that address the tough questions of disease diagnosis, prevention, and immunization. The volume looks at applications of deep learning for major medical challenges such as cancer detection and identification, birth asphyxia among neonates, kidney abnormalities, white blood cell segmentation, diabetic retinopathy detection, and Covid-19 diagnosis, prevention, and immunization. The volume discusses applications of deep learning in detection, diagnosis, intensive examination and evaluation, genomic sequencing, convolutional neural networks for image recognition and processing, and more for health issues such as kidney problems, brain tumors, lung damage, and breast cancer. The authors look at ML for brain tumor segmentation, in lung CT scans, in digital X-ray devices, and for logistic and transport systems for effective delivery of healthcare.
Book Synopsis Cancer Prediction for Industrial IoT 4.0 by : Meenu Gupta
Download or read book Cancer Prediction for Industrial IoT 4.0 written by Meenu Gupta and published by CRC Press. This book was released on 2021-12-31 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Artificial intelligence: A step forward in biomarker discovery and integration towards improved cancer diagnosis and treatment by : Mónica Hebe Vazquez-Levin
Download or read book Artificial intelligence: A step forward in biomarker discovery and integration towards improved cancer diagnosis and treatment written by Mónica Hebe Vazquez-Levin and published by Frontiers Media SA. This book was released on 2023-04-26 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Handbook of Deep Learning in Biomedical Engineering and Health Informatics by : E. Golden Julie
Download or read book Handbook of Deep Learning in Biomedical Engineering and Health Informatics written by E. Golden Julie and published by CRC Press. This book was released on 2021-09-22 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new volume discusses state-of-the-art deep learning techniques and approaches that can be applied in biomedical systems and health informatics. Deep learning in the biomedical field is an effective method of collecting and analyzing data that can be used for the accurate diagnosis of disease. This volume delves into a variety of applications, techniques, algorithms, platforms, and tools used in this area, such as image segmentation, classification, registration, and computer-aided analysis. The editors proceed on the principle that accurate diagnosis of disease depends on image acquisition and interpretation. There are many methods to get high resolution radiological images, but we are still lacking in automated image interpretation. Currently deep learning techniques are providing a feasible solution for automatic diagnosis of disease with good accuracy. Analyzing clinical data using deep learning techniques enables clinicians to diagnose diseases at an early stage and treat patients more effectively. Chapters explore such approaches as deep learning algorithms, convolutional neural networks and recurrent neural network architecture, image stitching techniques, deep RNN architectures, and more. This volume also depicts how deep learning techniques can be applied for medical diagnostics of several specific health scenarios, such as cancer, COVID-19, acute neurocutaneous syndrome, cardiovascular and neuro diseases, skin lesions and skin cancer, etc. Key features: Introduces important recent technological advancements in the field Describes the various techniques, platforms, and tools used in biomedical deep learning systems Includes informative case studies that help to explain the new technologies Handbook of Deep Learning in Biomedical Engineering and Health Informatics provides a thorough exploration of biomedical systems applied with deep learning techniques and will provide valuable information for researchers, medical and industry practitioners, academicians, and students.
Book Synopsis Brain Tumor MRI Image Segmentation Using Deep Learning Techniques by : Jyotismita Chaki
Download or read book Brain Tumor MRI Image Segmentation Using Deep Learning Techniques written by Jyotismita Chaki and published by Academic Press. This book was released on 2021-11-27 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Brain Tumor MRI Image Segmentation Using Deep Learning Techniques offers a description of deep learning approaches used for the segmentation of brain tumors. The book demonstrates core concepts of deep learning algorithms by using diagrams, data tables and examples to illustrate brain tumor segmentation. After introducing basic concepts of deep learning-based brain tumor segmentation, sections cover techniques for modeling, segmentation and properties. A focus is placed on the application of different types of convolutional neural networks, like single path, multi path, fully convolutional network, cascade convolutional neural networks, Long Short-Term Memory - Recurrent Neural Network and Gated Recurrent Units, and more. The book also highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in brain tumor segmentation. Provides readers with an understanding of deep learning-based approaches in the field of brain tumor segmentation, including preprocessing techniques Integrates recent advancements in the field, including the transformation of low-resolution brain tumor images into super-resolution images using deep learning-based methods, single path Convolutional Neural Network based brain tumor segmentation, and much more Includes coverage of Long Short-Term Memory (LSTM) based Recurrent Neural Network (RNN), Gated Recurrent Units (GRU) based Recurrent Neural Network (RNN), Generative Adversarial Networks (GAN), Auto Encoder based brain tumor segmentation, and Ensemble deep learning Model based brain tumor segmentation Covers research Issues and the future of deep learning-based brain tumor segmentation
Book Synopsis Artificial Intelligence in Cancer by : Smaranda Belciug
Download or read book Artificial Intelligence in Cancer written by Smaranda Belciug and published by Academic Press. This book was released on 2020-06-18 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence in Cancer: Diagnostic to Tailored Treatment provides theoretical concepts and practical techniques of AI and its applications in cancer management, building a roadmap on how to use AI in cancer at different stages of healthcare. It discusses topics such as the impactful role of AI during diagnosis and how it can support clinicians to make better decisions, AI tools to help pathologists identify exact types of cancer, how AI supports tumor profiling and can assist surgeons, and the gains in precision for oncologists using AI tools. Additionally, it provides information on AI used for survival and remission/recurrence analysis. The book is a valuable source for bioinformaticians, cancer researchers, oncologists, clinicians and members of the biomedical field who want to understand the promising field of AI applications in cancer management. Discusses over 20 real cancer examples, bringing state-of-the-art cancer cases in which AI was used to help the medical personnel Presents over 100 diagrams, making it easier to comprehend AI’s results on a specific problem through visual resources Explains AI algorithms in a friendly manner, thus helping the reader implement or use them in a specific cancer case
Book Synopsis Ultrasound in Oncology: Application of Big Data and Artificial Intelligence by : Hui-Xiong Xu
Download or read book Ultrasound in Oncology: Application of Big Data and Artificial Intelligence written by Hui-Xiong Xu and published by Frontiers Media SA. This book was released on 2022-02-09 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Artificial Intelligence in Breast Cancer Early Detection and Diagnosis by : Khalid Shaikh
Download or read book Artificial Intelligence in Breast Cancer Early Detection and Diagnosis written by Khalid Shaikh and published by Springer Nature. This book was released on 2020-12-04 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Machine Learning and Deep Learning Techniques for Medical Science by : K. Gayathri Devi
Download or read book Machine Learning and Deep Learning Techniques for Medical Science written by K. Gayathri Devi and published by CRC Press. This book was released on 2022-05-11 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: The application of machine learning is growing exponentially into every branch of business and science, including medical science. This book presents the integration of machine learning (ML) and deep learning (DL) algorithms that can be applied in the healthcare sector to reduce the time required by doctors, radiologists, and other medical professionals for analyzing, predicting, and diagnosing the conditions with accurate results. The book offers important key aspects in the development and implementation of ML and DL approaches toward developing prediction tools and models and improving medical diagnosis. The contributors explore the recent trends, innovations, challenges, and solutions, as well as case studies of the applications of ML and DL in intelligent system-based disease diagnosis. The chapters also highlight the basics and the need for applying mathematical aspects with reference to the development of new medical models. Authors also explore ML and DL in relation to artificial intelligence (AI) prediction tools, the discovery of drugs, neuroscience, diagnosis in multiple imaging modalities, and pattern recognition approaches to functional magnetic resonance imaging images. This book is for students and researchers of computer science and engineering, electronics and communication engineering, and information technology; for biomedical engineering researchers, academicians, and educators; and for students and professionals in other areas of the healthcare sector. Presents key aspects in the development and the implementation of ML and DL approaches toward developing prediction tools, models, and improving medical diagnosis Discusses the recent trends, innovations, challenges, solutions, and applications of intelligent system-based disease diagnosis Examines DL theories, models, and tools to enhance health information systems Explores ML and DL in relation to AI prediction tools, discovery of drugs, neuroscience, and diagnosis in multiple imaging modalities Dr. K. Gayathri Devi is a Professor at the Department of Electronics and Communication Engineering, Dr. N.G.P Institute of Technology, Tamil Nadu, India. Dr. Kishore Balasubramanian is an Assistant Professor (Senior Scale) at the Department of EEE at Dr. Mahalingam College of Engineering & Technology, Tamil Nadu, India. Dr. Le Anh Ngoc is a Director of Swinburne Innovation Space and Professor in Swinburne University of Technology (Vietnam).
Book Synopsis Computational Pathology for Precision Diagnosis, Treatment, and Prognosis of Cancer by : Jun Cheng
Download or read book Computational Pathology for Precision Diagnosis, Treatment, and Prognosis of Cancer written by Jun Cheng and published by Frontiers Media SA. This book was released on 2024-02-20 with total page 127 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Deep learning approaches in image-guided diagnosis for tumors by : Shahid Mumtaz
Download or read book Deep learning approaches in image-guided diagnosis for tumors written by Shahid Mumtaz and published by Frontiers Media SA. This book was released on 2023-03-13 with total page 173 pages. Available in PDF, EPUB and Kindle. Book excerpt: