Artificial Intelligence in Cancer

Artificial Intelligence in Cancer
Author: Smaranda Belciug
Publsiher: Academic Press
Total Pages: 318
Release: 2020-07-15
ISBN 10: 0128202017
ISBN 13: 9780128202012
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Cancer Book Review:

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
Author: Khalid Shaikh,Sabitha Krishnan,Rohit Thanki
Publsiher: Springer Nature
Total Pages: 107
Release: 2020-12-04
ISBN 10: 3030592081
ISBN 13: 9783030592080
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Breast Cancer Early Detection and Diagnosis Book Review:

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

Artificial Intelligence in Oncology Drug Discovery and Development

Artificial Intelligence in Oncology Drug Discovery and Development
Author: John Cassidy,Belle Taylor
Publsiher: BoD – Books on Demand
Total Pages: 192
Release: 2020-09-09
ISBN 10: 1789846897
ISBN 13: 9781789846898
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Oncology Drug Discovery and Development Book Review:

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 Intelligence Techniques in Breast Cancer Diagnosis and Prognosis

Artificial Intelligence Techniques in Breast Cancer Diagnosis and Prognosis
Author: Ashlesha Jain,Ajita Jain,Sandhya Jain
Publsiher: World Scientific
Total Pages: 330
Release: 2000
ISBN 10: 981024374X
ISBN 13: 9789810243746
Language: EN, FR, DE, ES & NL

Artificial Intelligence Techniques in Breast Cancer Diagnosis and Prognosis Book Review:

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.

Deep Learning for Cancer Diagnosis

Deep Learning for Cancer Diagnosis
Author: Utku Kose,Jafar Alzubi
Publsiher: Springer Nature
Total Pages: 300
Release: 2020-09-12
ISBN 10: 9811563217
ISBN 13: 9789811563218
Language: EN, FR, DE, ES & NL

Deep Learning for Cancer Diagnosis Book Review:

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.

Automation Control and Energy Efficiency in Complex Systems

Automation  Control and Energy Efficiency in Complex Systems
Author: Hamid Khayyam
Publsiher: MDPI
Total Pages: 242
Release: 2020-12-22
ISBN 10: 3039436279
ISBN 13: 9783039436279
Language: EN, FR, DE, ES & NL

Automation Control and Energy Efficiency in Complex Systems Book Review:

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.

Artificial Intelligence and Deep Learning in Pathology

Artificial Intelligence and Deep Learning in Pathology
Author: Stanley Cohen
Publsiher: Elsevier Health Sciences
Total Pages: 288
Release: 2020-06-02
ISBN 10: 0323675379
ISBN 13: 9780323675376
Language: EN, FR, DE, ES & NL

Artificial Intelligence and Deep Learning in Pathology Book Review:

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.

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

Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning
Author: Rani, Geeta,Tiwari, Pradeep Kumar
Publsiher: IGI Global
Total Pages: 586
Release: 2020-10-16
ISBN 10: 1799827437
ISBN 13: 9781799827436
Language: EN, FR, DE, ES & NL

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

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.

Machine Learning in Radiation Oncology

Machine Learning in Radiation Oncology
Author: Issam El Naqa,Ruijiang Li,Martin J. Murphy
Publsiher: Springer
Total Pages: 336
Release: 2015-06-19
ISBN 10: 3319183052
ISBN 13: 9783319183053
Language: EN, FR, DE, ES & NL

Machine Learning in Radiation Oncology Book Review:

​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.

Big Data in Radiation Oncology

Big Data in Radiation Oncology
Author: Jun Deng,Lei Xing
Publsiher: CRC Press
Total Pages: 289
Release: 2019-03-07
ISBN 10: 1351801120
ISBN 13: 9781351801126
Language: EN, FR, DE, ES & NL

Big Data in Radiation Oncology Book Review:

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.

Deep Learning for the Life Sciences

Deep Learning for the Life Sciences
Author: Bharath Ramsundar,Peter Eastman,Patrick Walters,Vijay Pande
Publsiher: O'Reilly Media
Total Pages: 238
Release: 2019-04-10
ISBN 10: 1492039802
ISBN 13: 9781492039808
Language: EN, FR, DE, ES & NL

Deep Learning for the Life Sciences Book Review:

Deep learning has already achieved remarkable results in many fields. Now it’s making waves throughout the sciences broadly and the life sciences in particular. This practical book teaches developers and scientists how to use deep learning for genomics, chemistry, biophysics, microscopy, medical analysis, and other fields. Ideal for practicing developers and scientists ready to apply their skills to scientific applications such as biology, genetics, and drug discovery, this book introduces several deep network primitives. You’ll follow a case study on the problem of designing new therapeutics that ties together physics, chemistry, biology, and medicine—an example that represents one of science’s greatest challenges. Learn the basics of performing machine learning on molecular data Understand why deep learning is a powerful tool for genetics and genomics Apply deep learning to understand biophysical systems Get a brief introduction to machine learning with DeepChem Use deep learning to analyze microscopic images Analyze medical scans using deep learning techniques Learn about variational autoencoders and generative adversarial networks Interpret what your model is doing and how it’s working

Artificial Intelligence for Data Driven Medical Diagnosis

Artificial Intelligence for Data Driven Medical Diagnosis
Author: Deepak Gupta,Utku Kose,Bao Le Nguyen,Siddhartha Bhattacharyya
Publsiher: Walter de Gruyter GmbH & Co KG
Total Pages: 326
Release: 2021-01-28
ISBN 10: 3110668386
ISBN 13: 9783110668384
Language: EN, FR, DE, ES & NL

Artificial Intelligence for Data Driven Medical Diagnosis Book Review:

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.

Big Data and Artificial Intelligence for Healthcare Applications

Big Data and Artificial Intelligence for Healthcare Applications
Author: Ankur Saxena,Nicolas Brault,Shazia Rashid
Publsiher: CRC Press
Total Pages: 286
Release: 2021-06-15
ISBN 10: 1000387313
ISBN 13: 9781000387315
Language: EN, FR, DE, ES & NL

Big Data and Artificial Intelligence for Healthcare Applications Book Review:

This book covers a wide range of topics on the role of Artificial Intelligence, Machine Learning, and Big Data for healthcare applications and deals with the ethical issues and concerns associated with it. This book explores the applications in different areas of healthcare and highlights the current research. "Big Data and Artificial Intelligence for Healthcare Applications" covers healthcare big data analytics, mobile health and personalized medicine, clinical trial data management and presents how Artificial Intelligence can be used for early disease diagnosis prediction and prognosis. It also offers some case studies that describes the application of Artificial Intelligence and Machine Learning in healthcare. Researchers, healthcare professionals, data scientists, systems engineers, students, programmers, clinicians, and policymakers will find this book of interest.

Artificial Neural Networks in Cancer Diagnosis Prognosis and Patient Management

Artificial Neural Networks in Cancer Diagnosis  Prognosis  and Patient Management
Author: R. N. G. Naguib,G. V. Sherbet
Publsiher: CRC Press
Total Pages: 216
Release: 2001-06-22
ISBN 10: 1420036386
ISBN 13: 9781420036381
Language: EN, FR, DE, ES & NL

Artificial Neural Networks in Cancer Diagnosis Prognosis and Patient Management Book Review:

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

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
Author: Lu, Zhongyu,Xu, Qiang,Al-Rajab, Murad,Chiazor, Lamogha
Publsiher: IGI Global
Total Pages: 263
Release: 2021-05-28
ISBN 10: 179987317X
ISBN 13: 9781799873174
Language: EN, FR, DE, ES & NL

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

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.

Target Discovery for Anticancer Therapy Facilitated by Artificial Intelligence

Target Discovery for Anticancer Therapy Facilitated by Artificial Intelligence
Author: Feng Zhu,Yu Zong Chen,Weiwei Xue
Publsiher: Frontiers Media SA
Total Pages: 218
Release: 2021-08-19
ISBN 10: 2889712001
ISBN 13: 9782889712007
Language: EN, FR, DE, ES & NL

Target Discovery for Anticancer Therapy Facilitated by Artificial Intelligence Book Review:

Artificial Intelligence in Medicine

Artificial Intelligence in Medicine
Author: Lei Xing,Maryellen L. Giger,James K. Min
Publsiher: Academic Press
Total Pages: 568
Release: 2020-09-03
ISBN 10: 0128212586
ISBN 13: 9780128212585
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Medicine Book Review:

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

Advanced AI Techniques and Applications in Bioinformatics

Advanced AI Techniques and Applications in Bioinformatics
Author: Loveleen Gaur,Arun Solanki,Samuel Fosso Wamba,Noor Zaman Jhanjhi
Publsiher: CRC Press
Total Pages: 282
Release: 2021-10-18
ISBN 10: 100046301X
ISBN 13: 9781000463019
Language: EN, FR, DE, ES & NL

Advanced AI Techniques and Applications in Bioinformatics Book Review:

The advanced AI techniques are essential for resolving various problematic aspects emerging in the field of bioinformatics. This book covers the recent approaches in artificial intelligence and machine learning methods and their applications in Genome and Gene editing, cancer drug discovery classification, and the protein folding algorithms among others. Deep learning, which is widely used in image processing, is also applicable in bioinformatics as one of the most popular artificial intelligence approaches. The wide range of applications discussed in this book are an indispensable resource for computer scientists, engineers, biologists, mathematicians, physicians, and medical informaticists. Features: Focusses on the cross-disciplinary relation between computer science and biology and the role of machine learning methods in resolving complex problems in bioinformatics Provides a comprehensive and balanced blend of topics and applications using various advanced algorithms Presents cutting-edge research methodologies in the area of AI methods when applied to bioinformatics and innovative solutions Discusses the AI/ML techniques, their use, and their potential for use in common and future bioinformatics applications Includes recent achievements in AI and bioinformatics contributed by a global team of researchers

Cervical Cancer

Cervical Cancer
Author: Rajamanickam Rajkumar
Publsiher: BoD – Books on Demand
Total Pages: 148
Release: 2021-11-17
ISBN 10: 1789853451
ISBN 13: 9781789853452
Language: EN, FR, DE, ES & NL

Cervical Cancer Book Review:

Although it is preventable and curable, cervical cancer is the fourth most common form of cancer among women worldwide. As such, the World Health Organization adopted a Cervical Cancer Elimination Initiative, which aims to eliminate cervical cancer by 2030. This book discusses plans, programs, strategies, solutions, research, and revolutions necessary to achieve this goal. Chapters cover such topics as epidemiology, HPV vaccination, screening and treatment, and prevention and control.

Cancer Nanotheranostics

Cancer Nanotheranostics
Author: Muthupandian Saravanan,Hamed Barabadi
Publsiher: Springer Nature
Total Pages: 368
Release: 2021-10-05
ISBN 10: 3030762637
ISBN 13: 9783030762636
Language: EN, FR, DE, ES & NL

Cancer Nanotheranostics Book Review:

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.