Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Artificial Intelligence In Pancreatic Disease Detection And Diagnosis And Personalized Incremental Learning In Medicine
Download Artificial Intelligence In Pancreatic Disease Detection And Diagnosis And Personalized Incremental Learning In Medicine full books in PDF, epub, and Kindle. Read online Artificial Intelligence In Pancreatic Disease Detection And Diagnosis And Personalized Incremental Learning In Medicine ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Artificial Intelligence in Pancreatic Disease Detection and Diagnosis, and Personalized Incremental Learning in Medicine by : Federica Proietto Salanitri
Download or read book Artificial Intelligence in Pancreatic Disease Detection and Diagnosis, and Personalized Incremental Learning in Medicine written by Federica Proietto Salanitri and published by Springer Nature. This book was released on with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis ARTIFICIAL INTELLIGENCE IN PANCREATIC DISEASE DETECTION AND. by :
Download or read book ARTIFICIAL INTELLIGENCE IN PANCREATIC DISEASE DETECTION AND. written by and published by . This book was released on 2024 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Artificial Intelligence in Medical Imaging by : Erik R. Ranschaert
Download or read book Artificial Intelligence in Medical Imaging written by Erik R. Ranschaert and published by Springer. This book was released on 2019-01-29 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis A Systematic Survey of Computer-Aided Diagnosis in Medicine: Past and Present Developments by : Juri Yanase
Download or read book A Systematic Survey of Computer-Aided Diagnosis in Medicine: Past and Present Developments written by Juri Yanase and published by Infinite Study. This book was released on with total page 51 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer-aided diagnosis (CAD) in medicine is the result of a large amount of effort expended in the interface of medicine and computer science. As some CAD systems in medicine try to emulate the diagnostic decision-making process of medical experts, they can be considered as expert systems in medicine.
Book Synopsis Artificial Intelligence in Medicine by : Lei Xing
Download or read book Artificial Intelligence in Medicine written by Lei Xing and published by Academic Press. This book was released on 2020-09-03 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Artificial Intelligence by : Jacob Parakilas
Download or read book Artificial Intelligence written by Jacob Parakilas and published by Chatham House (Formerly Riia). This book was released on 2018 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The rise of AI must be better managed in the near term in order to mitigate longer term risks and to ensure that AI does not reinforce existing inequalities"--Publisher.
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 Artificial Intelligence in Medicine by : Niklas Lidströmer
Download or read book Artificial Intelligence in Medicine written by Niklas Lidströmer and published by Springer. This book was released on 2022-03-17 with total page 1816 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a structured and analytical guide to the use of artificial intelligence in medicine. Covering all areas within medicine, the chapters give a systemic review of the history, scientific foundations, present advances, potential trends, and future challenges of artificial intelligence within a healthcare setting. Artificial Intelligence in Medicine aims to give readers the required knowledge to apply artificial intelligence to clinical practice. The book is relevant to medical students, specialist doctors, and researchers whose work will be affected by artificial intelligence.
Book Synopsis Genomics in Precision Medicine by : Shiv Sanjeevi
Download or read book Genomics in Precision Medicine written by Shiv Sanjeevi and published by Delve Publishing. This book was released on 2019-11 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genomics in Precision Medicine makes the people aware about the field of genomics and that of precision medicine, by taking the readers through all the details related to genomics and precision medicine. It also updates the readers about the various innovations that have taken place in the field of precision medicine and discusses the path that is to be followed further. Also discussed in the book is a review on the relation between the precision medicine and the mutations that drive it, delving on the various computational methods and conformational principles for the detection of the factors that drive cancer. It also discusses the various genetic mutations and epigenetic modifications and goes on to explore the various benefits and harms in the research on precision medicine.
Book Synopsis Artificial Intelligence in Healthcare by : Adam Bohr
Download or read book Artificial Intelligence in Healthcare written by Adam Bohr and published by Academic Press. This book was released on 2020-06-21 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Sex-Specific Analysis of Cardiovascular Function by : Peter L. M. Kerkhof
Download or read book Sex-Specific Analysis of Cardiovascular Function written by Peter L. M. Kerkhof and published by Springer. This book was released on 2018-07-26 with total page 734 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers together contributions from internationally renowned authors in the field of cardiovascular systems and provides crucial insight into the importance of sex- and gender-concepts during the analysis of patient data. This innovative title is the first to offer the elements necessary to consider sex-related properties in both clinical and basic studies regarding the heart and circulation on multiscale levels (i.e. molecular, cellular, electrophysiologically, neuroendocrine, immunoregulatory, organ, allometric, and modeling). Observed differences at (ultra)cellular and organ level are quantified, with focus on clinical relevance and implications for diagnosis and patient management. Since the cardiovascular system is of vital importance for all tissues, Sex-Specific Analysis of Cardiovascular Function is an essential source of information for clinicians, biologists, and biomedical investigators. The wide spectrum of differences described in this book will also act as an eye-opener and serve as a handbook for students, teachers, scientists and practitioners.
Book Synopsis Advancing the Science of Implementation Across the Cancer Continuum by : David A. Chambers (DPhil)
Download or read book Advancing the Science of Implementation Across the Cancer Continuum written by David A. Chambers (DPhil) and published by . This book was released on 2018 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: While many effective interventions have been developed with the potential to significantly reduce morbidity and mortality from cancer, they are of no benefit to the health of populations if they cannot be delivered. In response to this challenge, Advancing the Science of Implementation across the Cancer Continuum provides an overview of research that can improve the delivery of evidence-based interventions in cancer prevention, early detection, treatment, and survivorship. Chapters explore the field of implementation science and its application to practice, a broad synthesis of relevant research and case studies illustrating each cancer-focused topic area, and emerging issues at the intersection of research and practice in cancer. Both comprehensive and accessible, this book is an ideal resource for researchers, clinical and public health practitioners, medical and public health students, and health policymakers.
Book Synopsis Human Genetics and Genomics by : Bruce R. Korf
Download or read book Human Genetics and Genomics written by Bruce R. Korf and published by John Wiley & Sons. This book was released on 2012-11-19 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: This fourth edition of the best-selling textbook, Human Genetics and Genomics, clearly explains the key principles needed by medical and health sciences students, from the basis of molecular genetics, to clinical applications used in the treatment of both rare and common conditions. A newly expanded Part 1, Basic Principles of Human Genetics, focuses on introducing the reader to key concepts such as Mendelian principles, DNA replication and gene expression. Part 2, Genetics and Genomics in Medical Practice, uses case scenarios to help you engage with current genetic practice. Now featuring full-color diagrams, Human Genetics and Genomics has been rigorously updated to reflect today’s genetics teaching, and includes updated discussion of genetic risk assessment, “single gene” disorders and therapeutics. Key learning features include: Clinical snapshots to help relate science to practice 'Hot topics' boxes that focus on the latest developments in testing, assessment and treatment 'Ethical issues' boxes to prompt further thought and discussion on the implications of genetic developments 'Sources of information' boxes to assist with the practicalities of clinical research and information provision Self-assessment review questions in each chapter Accompanied by the Wiley E-Text digital edition (included in the price of the book), Human Genetics and Genomics is also fully supported by a suite of online resources at www.korfgenetics.com, including: Factsheets on 100 genetic disorders, ideal for study and exam preparation Interactive Multiple Choice Questions (MCQs) with feedback on all answers Links to online resources for further study Figures from the book available as PowerPoint slides, ideal for teaching purposes The perfect companion to the genetics component of both problem-based learning and integrated medical courses, Human Genetics and Genomics presents the ideal balance between the bio-molecular basis of genetics and clinical cases, and provides an invaluable overview for anyone wishing to engage with this fast-moving discipline.
Book Synopsis Deep Learning for Biomedical Applications by : Utku Kose
Download or read book Deep Learning for Biomedical Applications written by Utku Kose and published by CRC Press. This book was released on 2021-07-19 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a detailed reference on biomedical applications using Deep Learning. Because Deep Learning is an important actor shaping the future of Artificial Intelligence, its specific and innovative solutions for both medical and biomedical are very critical. This book provides a recent view of research works on essential, and advanced topics. The book offers detailed information on the application of Deep Learning for solving biomedical problems. It focuses on different types of data (i.e. raw data, signal-time series, medical images) to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis, image processing perspectives, and even genomics. It takes the reader through different sides of Deep Learning oriented solutions. The specific and innovative solutions covered in this book for both medical and biomedical applications are critical to scientists, researchers, practitioners, professionals, and educations who are working in the context of the topics.
Book Synopsis Deep Learning and Convolutional Neural Networks for Medical Image Computing by : Le Lu
Download or read book Deep Learning and Convolutional Neural Networks for Medical Image Computing written by Le Lu and published by Springer. This book was released on 2017-07-12 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks, with the theory supported by practical examples. Features: highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in medical image computing; discusses the insightful research experience of Dr. Ronald M. Summers; presents a comprehensive review of the latest research and literature; describes a range of different methods that make use of deep learning for object or landmark detection tasks in 2D and 3D medical imaging; examines a varied selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to interleaved text and image deep mining on a large-scale radiology image database.
Book Synopsis Intelligent Data Analysis in Medicine and Pharmacology by : Nada Lavrač
Download or read book Intelligent Data Analysis in Medicine and Pharmacology written by Nada Lavrač and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent data analysis, data mining and knowledge discovery in databases have recently gained the attention of a large number of researchers and practitioners. This is witnessed by the rapidly increasing number of submissions and participants at related conferences and workshops, by the emergence of new journals in this area (e.g., Data Mining and Knowledge Discovery, Intelligent Data Analysis, etc.), and by the increasing number of new applications in this field. In our view, the awareness of these challenging research fields and emerging technologies has been much larger in industry than in medicine and pharmacology. The main purpose of this book is to present the various techniques and methods that are available for intelligent data analysis in medicine and pharmacology, and to present case studies of their application. Intelligent Data Analysis in Medicine and Pharmacology consists of selected (and thoroughly revised) papers presented at the First International Workshop on Intelligent Data Analysis in Medicine and Pharmacology (IDAMAP-96) held in Budapest in August 1996 as part of the 12th European Conference on Artificial Intelligence (ECAI-96), IDAMAP-96 was organized with the motivation to gather scientists and practitioners interested in computational data analysis methods applied to medicine and pharmacology, aimed at narrowing the increasing gap between excessive amounts of data stored in medical and pharmacological databases on the one hand, and the interpretation, understanding and effective use of stored data on the other hand. Besides the revised Workshop papers, the book contains a selection of contributions by invited authors. The expected readership of the book is researchers and practitioners interested in intelligent data analysis, data mining, and knowledge discovery in databases, particularly those who are interested in using these technologies in medicine and pharmacology. Researchers and students in artificial intelligence and statistics should find this book of interest as well. Finally, much of the presented material will be interesting to physicians and pharmacologists challenged by new computational technologies, or simply in need of effectively utilizing the overwhelming volumes of data collected as a result of improved computer support in their daily professional practice.
Author :National Academies of Sciences, Engineering, and Medicine Publisher :National Academies Press ISBN 13 :0309457971 Total Pages :145 pages Book Rating :4.3/5 (94 download)
Book Synopsis The Drug Development Paradigm in Oncology by : National Academies of Sciences, Engineering, and Medicine
Download or read book The Drug Development Paradigm in Oncology written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2018-02-12 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in cancer research have led to an improved understanding of the molecular mechanisms underpinning the development of cancer and how the immune system responds to cancer. This influx of research has led to an increasing number and variety of therapies in the drug development pipeline, including targeted therapies and associated biomarker tests that can select which patients are most likely to respond, and immunotherapies that harness the body's immune system to destroy cancer cells. Compared with standard chemotherapies, these new cancer therapies may demonstrate evidence of benefit and clearer distinctions between efficacy and toxicity at an earlier stage of development. However, there is a concern that the traditional processes for cancer drug development, evaluation, and regulatory approval could impede or delay the use of these promising cancer treatments in clinical practice. This has led to a number of effortsâ€"by patient advocates, the pharmaceutical industry, and the Food and Drug Administration (FDA)â€"to accelerate the review of promising new cancer therapies, especially for cancers that currently lack effective treatments. However, generating the necessary data to confirm safety and efficacy during expedited drug development programs can present a unique set of challenges and opportunities. To explore this new landscape in cancer drug development, the National Academies of Sciences, Engineering, and Medicine developed a workshop held in December 2016. This workshop convened cancer researchers, patient advocates, and representatives from industry, academia, and government to discuss challenges with traditional approaches to drug development, opportunities to improve the efficiency of drug development, and strategies to enhance the information available about a cancer therapy throughout its life cycle in order to improve its use in clinical practice. This publication summarizes the presentations and discussions from the workshop.