Artificial Intelligence In Pathology

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Artificial Intelligence and Machine Learning for Digital Pathology

Author : Andreas Holzinger,Randy Goebel,Michael Mengel,Heimo Müller
Publisher : Springer Nature
Page : 351 pages
File Size : 54,7 Mb
Release : 2020-06-24
Category : Computers
ISBN : 9783030504021

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Artificial Intelligence and Machine Learning for Digital Pathology by Andreas Holzinger,Randy Goebel,Michael Mengel,Heimo Müller Pdf

Data driven Artificial Intelligence (AI) and Machine Learning (ML) in digital pathology, radiology, and dermatology is very promising. In specific cases, for example, Deep Learning (DL), even exceeding human performance. However, in the context of medicine it is important for a human expert to verify the outcome. Consequently, there is a need for transparency and re-traceability of state-of-the-art solutions to make them usable for ethical responsible medical decision support. Moreover, big data is required for training, covering a wide spectrum of a variety of human diseases in different organ systems. These data sets must meet top-quality and regulatory criteria and must be well annotated for ML at patient-, sample-, and image-level. Here biobanks play a central and future role in providing large collections of high-quality, well-annotated samples and data. The main challenges are finding biobanks containing ‘‘fit-for-purpose’’ samples, providing quality related meta-data, gaining access to standardized medical data and annotations, and mass scanning of whole slides including efficient data management solutions.

Artificial Intelligence and Deep Learning in Pathology

Author : Stanley Cohen
Publisher : Elsevier Health Sciences
Page : 290 pages
File Size : 54,9 Mb
Release : 2020-06-02
Category : Medical
ISBN : 9780323675376

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Artificial Intelligence and Deep Learning in Pathology by Stanley Cohen Pdf

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.

Artificial Intelligence Applications In Human Pathology

Author : Ralf Huss,Michael Grunkin
Publisher : World Scientific
Page : 337 pages
File Size : 49,5 Mb
Release : 2022-03-04
Category : Science
ISBN : 9781800611405

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Artificial Intelligence Applications In Human Pathology by Ralf Huss,Michael Grunkin Pdf

Artificial Intelligence Applications in Human Pathology deals with the latest topics in biomedical research and clinical cancer diagnostics. With chapters provided by true international experts in the field, this book gives real examples of the implementation of AI and machine learning in human pathology.Advances in machine learning and AI in general have propelled computational and general pathology research. Today, computer systems approach the diagnostic levels achieved by humans for certain well-defined tasks in pathology. At the same time, pathologists are faced with an increased workload both quantitatively (numbers of cases) and qualitatively (the amount of work per case, with increasing treatment options and the type of data delivered by pathologists also expected to become more fine-grained). AI will support and leverage mathematical tools and implement data-driven methods as a center for data interpretation in modern tissue diagnosis and pathology. Digital or computational pathology will also foster the training of future computational pathologists, those with both pathology and non-pathology backgrounds, who will eventually decide that AI-based pathology will serve as an indispensable hub for data-related research in a global health care system.Some of the specific topics explored within include an introduction to DL as applied to Pathology, Standardized Tissue Sampling for Automated Analysis, integrating Computational Pathology into Histopathology workflows. Readers will also find examples of specific techniques applied to specific diseases that will aid their research and treatments including but not limited to; Tissue Cartography for Colorectal Cancer, Ki-67 Measurements in Breast Cancer, and Light-Sheet Microscopy as applied to Virtual Histology.The key role for pathologists in tissue diagnostics will prevail and even expand through interdisciplinary work and the intuitive use of an advanced and interoperating (AI-supported) pathology workflow delivering novel and complex features that will serve the understanding of individual diseases and of course the patient.

Digital Pathology

Author : Liron Pantanowitz,Anil V. Parwani
Publisher : Unknown
Page : 304 pages
File Size : 49,9 Mb
Release : 2017
Category : Medical informatics
ISBN : 0891896104

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Digital Pathology by Liron Pantanowitz,Anil V. Parwani Pdf

The definitive, complete reference of digital pathology! An extraordinarily comprehensive and complete book for individuals with anything from minimal knowledge to deep, accomplished experience in digital pathology. Easy to read and plainly written, Digital Pathology examines the history and technological evolution of digital pathology, from the birth of scanning technology and telepathology to three-dimensional imaging on large multi-touch displays and computer aided diagnosis. A must-have book for anyone wishing to learn more about and work in this exciting and critical information environment including pathologists, laboratory professionals, students and any other medical practitioners with a particular interest in the history and future of digital pathology. It can also be a useful reference for anyone, medical or non-medical, who have an interest in learning more about the field. Digital pathology is truly a game changer, and this book is a crucial tool for anyone wishing to know more. Subjects discussed in depth include: Static digital imaging; basics and clinical use. Digital imaging processes. Telepathology. While slide imaging. Clinical applications of whole slide imaging. Digital pathology for educational, quality improvement, research and other settings. Forensic digital imaging.

Deep Medicine

Author : Eric Topol
Publisher : Basic Books
Page : 373 pages
File Size : 53,9 Mb
Release : 2019-03-12
Category : Health & Fitness
ISBN : 9781541644649

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Deep Medicine by Eric Topol Pdf

A Science Friday pick for book of the year, 2019 One of America's top doctors reveals how AI will empower physicians and revolutionize patient care Medicine has become inhuman, to disastrous effect. The doctor-patient relationship--the heart of medicine--is broken: doctors are too distracted and overwhelmed to truly connect with their patients, and medical errors and misdiagnoses abound. In Deep Medicine, leading physician Eric Topol reveals how artificial intelligence can help. AI has the potential to transform everything doctors do, from notetaking and medical scans to diagnosis and treatment, greatly cutting down the cost of medicine and reducing human mortality. By freeing physicians from the tasks that interfere with human connection, AI will create space for the real healing that takes place between a doctor who can listen and a patient who needs to be heard. Innovative, provocative, and hopeful, Deep Medicine shows us how the awesome power of AI can make medicine better, for all the humans involved.

Digital Pathology

Author : Constantino Carlos Reyes-Aldasoro,Andrew Janowczyk,Mitko Veta,Peter Bankhead,Korsuk Sirinukunwattana
Publisher : Springer
Page : 192 pages
File Size : 46,5 Mb
Release : 2019-07-03
Category : Computers
ISBN : 9783030239374

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Digital Pathology by Constantino Carlos Reyes-Aldasoro,Andrew Janowczyk,Mitko Veta,Peter Bankhead,Korsuk Sirinukunwattana Pdf

This book constitutes the refereed proceedings of the 15th European Congress on Digital Pathology, ECDP 2019, held in Warwick, UK in April 2019. The 21 full papers presented in this volume were carefully reviewed and selected from 30 submissions. The congress theme will be Accelerating Clinical Deployment, with a focus on computational pathology and leveraging the power of big data and artificial intelligence to bridge the gaps between research, development, and clinical uptake.

Artificial intelligence in digital pathology image analysis

Author : Min Tang,Jialiang Yang,Li Xiao
Publisher : Frontiers Media SA
Page : 161 pages
File Size : 44,9 Mb
Release : 2023-05-03
Category : Medical
ISBN : 9782832522486

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Artificial intelligence in digital pathology image analysis by Min Tang,Jialiang Yang,Li Xiao Pdf

Artificial Intelligence in Healthcare

Author : Adam Bohr,Kaveh Memarzadeh
Publisher : Academic Press
Page : 385 pages
File Size : 51,9 Mb
Release : 2020-06-21
Category : Computers
ISBN : 9780128184394

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Artificial Intelligence in Healthcare by Adam Bohr,Kaveh Memarzadeh Pdf

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

Smart Systems for Industrial Applications

Author : C. Venkatesh,N. Rengarajan,P. Ponmurugan,S. Balamurugan
Publisher : John Wiley & Sons
Page : 311 pages
File Size : 44,7 Mb
Release : 2022-01-07
Category : Computers
ISBN : 9781119762041

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Smart Systems for Industrial Applications by C. Venkatesh,N. Rengarajan,P. Ponmurugan,S. Balamurugan Pdf

SMART SYSTEMS FOR INDUSTRIAL APPLICATIONS The prime objective of this book is to provide an insight into the role and advancements of artificial intelligence in electrical systems and future challenges. The book covers a broad range of topics about AI from a multidisciplinary point of view, starting with its history and continuing on to theories about artificial vs. human intelligence, concepts, and regulations concerning AI, human-machine distribution of power and control, delegation of decisions, the social and economic impact of AI, etc. The prominent role that AI plays in society by connecting people through technologies is highlighted in this book. It also covers key aspects of various AI applications in electrical systems in order to enable growth in electrical engineering. The impact that AI has on social and economic factors is also examined from various perspectives. Moreover, many intriguing aspects of AI techniques in different domains are covered such as e-learning, healthcare, smart grid, virtual assistance, etc. Audience The book will be of interest to researchers and postgraduate students in artificial intelligence, electrical and electronic engineering, as well as those engineers working in the application areas such as healthcare, energy systems, education, and others.

Artificial Intelligence in the Clinical Laboratory: Current Practice and Emerging Opportunities, An Issue of the Clinics in Laboratory Medicine, E-Book

Author : Jason Baron
Publisher : Elsevier Health Sciences
Page : 161 pages
File Size : 51,6 Mb
Release : 2023-02-10
Category : Medical
ISBN : 9780323939843

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Artificial Intelligence in the Clinical Laboratory: Current Practice and Emerging Opportunities, An Issue of the Clinics in Laboratory Medicine, E-Book by Jason Baron Pdf

In this issue, guest editors bring their considerable expertise to this important topic. Provides in-depth reviews on the latest updates in the field, providing actionable insights for clinical practice. Presents the latest information on this timely, focused topic under the leadership of experienced editors in the field. Authors synthesize

Artificial Intelligence in Medical Imaging

Author : Erik R. Ranschaert,Sergey Morozov,Paul R. Algra
Publisher : Springer
Page : 373 pages
File Size : 54,8 Mb
Release : 2019-01-29
Category : Medical
ISBN : 9783319948782

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Artificial Intelligence in Medical Imaging by Erik R. Ranschaert,Sergey Morozov,Paul R. Algra Pdf

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 Pathology

Author : Stanley Cohen,Chhavi Chauhan
Publisher : Elsevier
Page : 0 pages
File Size : 43,8 Mb
Release : 2024-06-01
Category : Science
ISBN : 032395359X

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Artificial Intelligence in Pathology by Stanley Cohen,Chhavi Chauhan Pdf

Artificial Intelligence in Pathology: Principles and Applications provides a strong foundation of core artificial intelligence principles and their applications in the field of digital pathology. This is a reference of current and emerging use of AI in digital pathology as well as the emerging utility of quantum artificial intelligence and neuromorphic computing in digital pathology. It is a must-have educational resource for lay public, researchers, academicians, practitioners, policymakers, key administrators, and vendors to stay current with the shifting landscapes within the emerging field of digital pathology. It is also of use to workers in other diagnostic imaging areas such as radiology. This resource covers various aspects of the use of AI in pathology, including but not limited to the basic principles, advanced applications, challenges in the development, deployment, adoption, and scalability of AI-based models in pathology, the innumerous benefits of applying and integrating AI in the practice of pathology, ethical considerations for the safe adoption and deployment of AI in pathology.

Artificial Intelligence and Machine Learning in Public Healthcare

Author : KC Santosh,Loveleen Gaur
Publisher : Springer Nature
Page : 93 pages
File Size : 48,8 Mb
Release : 2022-01-01
Category : Technology & Engineering
ISBN : 9789811667688

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Artificial Intelligence and Machine Learning in Public Healthcare by KC Santosh,Loveleen Gaur Pdf

This book discusses and evaluates AI and machine learning (ML) algorithms in dealing with challenges that are primarily related to public health. It also helps find ways in which we can measure possible consequences and societal impacts by taking the following factors into account: open public health issues and common AI solutions (with multiple case studies, such as TB and SARS: COVID-19), AI in sustainable health care, AI in precision medicine and data privacy issues. Public health requires special attention as it drives economy and education system. COVID-19 is an example—a truly infectious disease outbreak. The vision of WHO is to create public health services that can deal with abovementioned crucial challenges by focusing on the following elements: health protection, disease prevention and health promotion. For these issues, in the big data analytics era, AI and ML tools/techniques have potential to improve public health (e.g., existing healthcare solutions and wellness services). In other words, they have proved to be valuable tools not only to analyze/diagnose pathology but also to accelerate decision-making procedure especially when we consider resource-constrained regions.

Histology for Pathologists

Author : Stacey E. Mills
Publisher : Lippincott Williams & Wilkins
Page : 3002 pages
File Size : 47,9 Mb
Release : 2012-07-16
Category : Medical
ISBN : 9781451177800

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Histology for Pathologists by Stacey E. Mills Pdf

A strong grounding in basic histology is essential for all pathologists. However, there had always been a gap between histology and pathology in which histologic information specifically for the pathologist was often lacking. Histology for Pathologists deals with the microscopic features of normal human tissues, from the perspective of the surgical pathologist. This is the only text that uses human (vs. animal) tissues for the histology. It is the best reference in the literature for information on normal histology, and, as such, is essential for all clinical pathologists. Written by pathologists for pathologists, the new edition updates the pathologist's understanding of normal histology up to date with the incremental advances made in the last five years. The 3rd edition has become a "classic" purchased by virtually all residents beginning their pathology training, as well as pathologists in practice. The 4th edition builds on that substantial foundation. The table of contents remains essentially the same with the exception of some changes in authorship.

Data Analytics in Bioinformatics

Author : Rabinarayan Satpathy,Tanupriya Choudhury,Suneeta Satpathy,Sachi Nandan Mohanty,Xiaobo Zhang
Publisher : John Wiley & Sons
Page : 433 pages
File Size : 40,5 Mb
Release : 2021-01-20
Category : Computers
ISBN : 9781119785606

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Data Analytics in Bioinformatics by Rabinarayan Satpathy,Tanupriya Choudhury,Suneeta Satpathy,Sachi Nandan Mohanty,Xiaobo Zhang Pdf

Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics approximating classification and prediction of disease, feature selection, dimensionality reduction, gene selection and classification of microarray data and many more.