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Artificial Intelligence In Cancer

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Artificial Intelligence in Cancer

Artificial Intelligence in Cancer Book
Author : Smaranda Belciug
Publisher : Academic Press
Release : 2020-07-15
ISBN : 0128202017
Language : En, Es, Fr & De

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Book Description :

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

Artificial Intelligence in Breast Cancer Early Detection and Diagnosis

Artificial Intelligence in Breast Cancer Early Detection and Diagnosis Book
Author : Khalid Shaikh,Sabitha Krishnan,Rohit Thanki
Publisher : Springer Nature
Release : 2020-12-04
ISBN : 3030592081
Language : En, Es, Fr & De

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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

Deep Learning for Cancer Diagnosis

Deep Learning for Cancer Diagnosis Book
Author : Utku Kose,Jafar Alzubi
Publisher : Springer Nature
Release : 2020-09-12
ISBN : 9811563217
Language : En, Es, Fr & De

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Book Description :

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.

Artificial Intelligence Techniques in Breast Cancer Diagnosis and Prognosis

Artificial Intelligence Techniques in Breast Cancer Diagnosis and Prognosis Book
Author : Ashlesha Jain,Ajita Jain,Sandhya Jain
Publisher : World Scientific
Release : 2000
ISBN : 981024374X
Language : En, Es, Fr & De

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Book Description :

The main aim of this book is to present a sample of recent research on the application of novel artificial intelligence paradigms to the diagnosis and prognosis of breast cancer. These paradigms include neural networks, fuzzy logic and evolutionary computing. Artificial intelligence techniques offer advantages ? such as adaptation, fault tolerance, learning and human-like behavior ? over conventional computing techniques. The idea is to combine the pathological, intelligent and statistical approaches to enable simple and accurate diagnosis and prognosis.This book is the first of its kind on the topic of artificial intelligence in breast cancer. It presents the applications of artificial intelligence in breast cancer diagnosis and prognosis, and includes state-of-the-art concepts in the field. It contains contributions from Australia, Germany, Italy, UK and the USA.

Artificial Intelligence in Oncology Drug Discovery and Development

Artificial Intelligence in Oncology Drug Discovery and Development Book
Author : John Cassidy,Belle Taylor
Publisher : BoD – Books on Demand
Release : 2020-09-09
ISBN : 1789846897
Language : En, Es, Fr & De

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Book Description :

There exists a profound conflict at the heart of oncology drug development. The efficiency of the drug development process is falling, leading to higher costs per approved drug, at the same time personalised medicine is limiting the target market of each new medicine. Even as the global economic burden of cancer increases, the current paradigm in drug development is unsustainable. In this book, we discuss the development of techniques in machine learning for improving the efficiency of oncology drug development and delivering cost-effective precision treatment. We consider how to structure data for drug repurposing and target identification, how to improve clinical trials and how patients may view artificial intelligence.

Artificial Neural Networks in Cancer Diagnosis Prognosis and Patient Management

Artificial Neural Networks in Cancer Diagnosis  Prognosis  and Patient Management Book
Author : R. N. G. Naguib,G. V. Sherbet
Publisher : CRC Press
Release : 2001-06-22
ISBN : 1420036386
Language : En, Es, Fr & De

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Book Description :

The potential value of artificial neural networks (ANN) as a predictor of malignancy has begun to receive increased recognition. Research and case studies can be found scattered throughout a multitude of journals. Artificial Neural Networks in Cancer Diagnosis, Prognosis, and Patient Management brings together the work of top researchers - primaril

Artificial Intelligence and Deep Learning in Pathology

Artificial Intelligence and Deep Learning in Pathology Book
Author : Stanley Cohen
Publisher : Elsevier Health Sciences
Release : 2020-06-02
ISBN : 0323675379
Language : En, Es, Fr & De

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Book Description :

Recent advances in computational algorithms, along with the advent of whole slide imaging as a platform for embedding artificial intelligence (AI), are transforming pattern recognition and image interpretation for diagnosis and prognosis. Yet most pathologists have just a passing knowledge of data mining, machine learning, and AI, and little exposure to the vast potential of these powerful new tools for medicine in general and pathology in particular. In Artificial Intelligence and Deep Learning in Pathology, Dr. Stanley Cohen covers the nuts and bolts of all aspects of machine learning, up to and including AI, bringing familiarity and understanding to pathologists at all levels of experience. Focuses heavily on applications in medicine, especially pathology, making unfamiliar material accessible and avoiding complex mathematics whenever possible. Covers digital pathology as a platform for primary diagnosis and augmentation via deep learning, whole slide imaging for 2D and 3D analysis, and general principles of image analysis and deep learning. Discusses and explains recent accomplishments such as algorithms used to diagnose skin cancer from photographs, AI-based platforms developed to identify lesions of the retina, using computer vision to interpret electrocardiograms, identifying mitoses in cancer using learning algorithms vs. signal processing algorithms, and many more.

Machine Learning in Radiation Oncology

Machine Learning in Radiation Oncology Book
Author : Issam El Naqa,Ruijiang Li,Martin J. Murphy
Publisher : Springer
Release : 2015-06-19
ISBN : 3319183052
Language : En, Es, Fr & De

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Book Description :

​This book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory, methods, and a variety of applications in medical physics and radiotherapy. An introductory section explains machine learning, reviews supervised and unsupervised learning methods, discusses performance evaluation, and summarizes potential applications in radiation oncology. Detailed individual sections are then devoted to the use of machine learning in quality assurance; computer-aided detection, including treatment planning and contouring; image-guided radiotherapy; respiratory motion management; and treatment response modeling and outcome prediction. The book will be invaluable for students and residents in medical physics and radiation oncology and will also appeal to more experienced practitioners and researchers and members of applied machine learning communities.

Novel Methods for Oncologic Imaging Analysis Radiomics Machine Learning and Artificial Intelligence

Novel Methods for Oncologic Imaging Analysis  Radiomics  Machine Learning  and Artificial Intelligence Book
Author : Xuelei Ma,Lei Deng,Rong Tian,Chunxiao Guo
Publisher : Frontiers Media SA
Release : 2021-09-23
ISBN : 2889713474
Language : En, Es, Fr & De

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Book Description :

Download Novel Methods for Oncologic Imaging Analysis Radiomics Machine Learning and Artificial Intelligence book written by Xuelei Ma,Lei Deng,Rong Tian,Chunxiao Guo, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Machine Learning in Cancer Research With Applications in Colon Cancer and Big Data Analysis

Machine Learning in Cancer Research With Applications in Colon Cancer and Big Data Analysis Book
Author : Lu, Zhongyu,Xu, Qiang,Al-Rajab, Murad,Chiazor, Lamogha
Publisher : IGI Global
Release : 2021-05-28
ISBN : 179987317X
Language : En, Es, Fr & De

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Book Description :

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.

Automation Control and Energy Efficiency in Complex Systems

Automation  Control and Energy Efficiency in Complex Systems Book
Author : Hamid Khayyam
Publisher : MDPI
Release : 2020-12-22
ISBN : 3039436279
Language : En, Es, Fr & De

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Book Description :

This book is aimed at serving researchers, engineers, scientists, and engineering graduate and PhD students of engineering and physical science together with individuals interested in engineering and science. This book focuses on the application of engineering methods to complex systems including transportation, building, and manufacturing, with approaches representing a wide variety of disciplines of engineering and science. Throughout the book, great emphases are placed on engineering applications of complex systems, as well as the methodologies of automation, including artificial intelligence, automated and intelligent control, energy analysis, energy modelling, energy management, and optimised energy efficiency. The significant impact of recent studies that have been selected for presentation are of high interest in engineering complex systems. An attempt has been made to expose the reading audience of engineers and researchers to a broad range of theoretical and practical topics. The topics contained in the present book are of specific interest to engineers who are seeking expertise in transportation, building, and manufacturing technologies as well as mathematical modelling of complex systems, engineering approaches to engineering complex problems, automation via artificial intelligence methods, automated and intelligent control, and energy systems. The primary audience of this book are researchers, graduate students, and engineers in mechanical engineering, control engineering, computer engineering, electrical engineering, and science disciplines. In particular, the book can be used for training graduate and PhD students as well as senior undergraduate students to enhance their knowledge by taking a graduate or advanced undergraduate course in the areas of complex systems, control systems, energy systems, and engineering applications. The covered research topics are also of interest to engineers and academia who are seeking to expand their expertise in these areas.

Big Data in Radiation Oncology

Big Data in Radiation Oncology Book
Author : Jun Deng,Lei Xing
Publisher : CRC Press
Release : 2019-03-07
ISBN : 1351801120
Language : En, Es, Fr & De

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Book Description :

Big Data in Radiation Oncology gives readers an in-depth look into how big data is having an impact on the clinical care of cancer patients. While basic principles and key analytical and processing techniques are introduced in the early chapters, the rest of the book turns to clinical applications, in particular for cancer registries, informatics, radiomics, radiogenomics, patient safety and quality of care, patient-reported outcomes, comparative effectiveness, treatment planning, and clinical decision-making. More features of the book are: Offers the first focused treatment of the role of big data in the clinic and its impact on radiation therapy. Covers applications in cancer registry, radiomics, patient safety, quality of care, treatment planning, decision making, and other key areas. Discusses the fundamental principles and techniques for processing and analysis of big data. Address the use of big data in cancer prevention, detection, prognosis, and management. Provides practical guidance on implementation for clinicians and other stakeholders. Dr. Jun Deng is a professor at the Department of Therapeutic Radiology of Yale University School of Medicine and an ABR board certified medical physicist at Yale-New Haven Hospital. He has received numerous honors and awards such as Fellow of Institute of Physics in 2004, AAPM Medical Physics Travel Grant in 2008, ASTRO IGRT Symposium Travel Grant in 2009, AAPM-IPEM Medical Physics Travel Grant in 2011, and Fellow of AAPM in 2013. Lei Xing, Ph.D., is the Jacob Haimson Professor of Medical Physics and Director of Medical Physics Division of Radiation Oncology Department at Stanford University. His research has been focused on inverse treatment planning, tomographic image reconstruction, CT, optical and PET imaging instrumentations, image guided interventions, nanomedicine, and applications of molecular imaging in radiation oncology. Dr. Xing is on the editorial boards of a number of journals in radiation physics and medical imaging, and is recipient of numerous awards, including the American Cancer Society Research Scholar Award, The Whitaker Foundation Grant Award, and a Max Planck Institute Fellowship.

Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning

Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning Book
Author : Rani, Geeta,Tiwari, Pradeep Kumar
Publisher : IGI Global
Release : 2020-10-16
ISBN : 1799827437
Language : En, Es, Fr & De

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Book Description :

By applying data analytics techniques and machine learning algorithms to predict disease, medical practitioners can more accurately diagnose and treat patients. However, researchers face problems in identifying suitable algorithms for pre-processing, transformations, and the integration of clinical data in a single module, as well as seeking different ways to build and evaluate models. The Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning is a pivotal reference source that explores the application of algorithms to making disease predictions through the identification of symptoms and information retrieval from images such as MRIs, ECGs, EEGs, etc. Highlighting a wide range of topics including clinical decision support systems, biomedical image analysis, and prediction models, this book is ideally designed for clinicians, physicians, programmers, computer engineers, IT specialists, data analysts, hospital administrators, researchers, academicians, and graduate and post-graduate students.

Advanced Machine Learning Approaches in Cancer Prognosis

Advanced Machine Learning Approaches in Cancer Prognosis Book
Author : Janmenjoy Nayak,Margarita N. Favorskaya,Seema Jain,Bighnaraj Naik,Manohar Mishra
Publisher : Springer Nature
Release : 2021-05-29
ISBN : 3030719758
Language : En, Es, Fr & De

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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.

Artificial Intelligence in Medical Imaging

Artificial Intelligence in Medical Imaging Book
Author : Erik R. Ranschaert,Sergey Morozov,Paul R. Algra
Publisher : Springer
Release : 2019-01-29
ISBN : 3319948784
Language : En, Es, Fr & De

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Book Description :

This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.

Artificial Intelligence in Healthcare

Artificial Intelligence in Healthcare Book
Author : Adam Bohr,Kaveh Memarzadeh
Publisher : Academic Press
Release : 2020-06-21
ISBN : 0128184396
Language : En, Es, Fr & De

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Book Description :

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data

Artificial Intelligence for Data Driven Medical Diagnosis

Artificial Intelligence for Data Driven Medical Diagnosis Book
Author : Deepak Gupta,Utku Kose,Bao Le Nguyen,Siddhartha Bhattacharyya
Publisher : Walter de Gruyter GmbH & Co KG
Release : 2021-02-08
ISBN : 3110668327
Language : En, Es, Fr & De

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Book Description :

This book collects research works of data-driven medical diagnosis done via Artificial Intelligence based solutions, such as Machine Learning, Deep Learning and Intelligent Optimization. Physical devices powered with Artificial Intelligence are gaining importance in diagnosis and healthcare. Medical data from different sources can also be analyzed via Artificial Intelligence techniques for more effective results.

Artificial Intelligence in Medicine

Artificial Intelligence in Medicine Book
Author : Lei Xing,Maryellen L. Giger,James K. Min
Publisher : Academic Press
Release : 2020-09-03
ISBN : 0128212586
Language : En, Es, Fr & De

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Book Description :

Artificial Intelligence Medicine: Technical Basis and Clinical Applications presents a comprehensive overview of the field, ranging from its history and technical foundations, to specific clinical applications and finally to prospects. Artificial Intelligence (AI) is expanding across all domains at a breakneck speed. Medicine, with the availability of large multidimensional datasets, lends itself to strong potential advancement with the appropriate harnessing of AI. The integration of AI can occur throughout the continuum of medicine: from basic laboratory discovery to clinical application and healthcare delivery. Integrating AI within medicine has been met with both excitement and scepticism. By understanding how AI works, and developing an appreciation for both limitations and strengths, clinicians can harness its computational power to streamline workflow and improve patient care. It also provides the opportunity to improve upon research methodologies beyond what is currently available using traditional statistical approaches. On the other hand, computers scientists and data analysts can provide solutions, but often lack easy access to clinical insight that may help focus their efforts. This book provides vital background knowledge to help bring these two groups together, and to engage in more streamlined dialogue to yield productive collaborative solutions in the field of medicine. Provides history and overview of artificial intelligence, as narrated by pioneers in the field Discusses broad and deep background and updates on recent advances in both medicine and artificial intelligence that enabled the application of artificial intelligence Addresses the ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach

Healthcare and Artificial Intelligence

Healthcare and Artificial Intelligence Book
Author : Bernard Nordlinger,Cédric Villani,Daniela Rus
Publisher : Springer Nature
Release : 2020-03-17
ISBN : 3030321614
Language : En, Es, Fr & De

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Book Description :

This book provides an overview of the role of AI in medicine and, more generally, of issues at the intersection of mathematics, informatics, and medicine. It is intended for AI experts, offering them a valuable retrospective and a global vision for the future, as well as for non-experts who are curious about this timely and important subject. Its goal is to provide clear, objective, and reasonable information on the issues covered, avoiding any fantasies that the topic “AI” might evoke. In addition, the book seeks to provide a broad kaleidoscopic perspective, rather than deep technical details.

Cancer Nanotheranostics

Cancer Nanotheranostics Book
Author : Muthupandian Saravanan,Hamed Barabadi
Publisher : Springer Nature
Release : 2021-10-05
ISBN : 3030762637
Language : En, Es, Fr & De

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Book Description :

Cancer Nanotheranostics, Volume 2 continues the discussion of the important work being done in this field of cancer nanotechnology. The contents of these two volumes are explained in detail as follows. In the first volume of Cancer Nanotheranostics, we discuss the role of different nanomaterials for cancer therapy including lipid-based nanomaterials, protein and peptide-based nanomaterials, polymer-based nanomaterials, metal-organic nanomaterials, porphyrin-based nanomaterials, metal-based nanomaterials, silica-based nanomaterials, exosome-based nanomaterials, and nano-antibodies. This important second volume discusses nano-based diagnosis of cancer, nano-oncology for clinical applications, nano-immunotherapy, nano-based photothermal cancer therapy, nanoerythrosomes for cancer drug delivery, regulatory perspectives of nanomaterials, limitations of cancer nanotheranostics, safety of nanobiomaterials for cancer nanotheranostics, multifunctional nanomaterials for targeting cancer nanotheranostics, and the role of artificial intelligence in cancer nanotheranostics. Volume 2 is a vital continuation of this two-volume set. Together, these two volumes create a comprehensive and unique examination of this important area of research.