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Author: Ralf Huss Publisher: World Scientific ISBN: 1800611404 Category : Science Languages : en Pages : 337
Book Description
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.
Author: Ralf Huss Publisher: World Scientific ISBN: 1800611404 Category : Science Languages : en Pages : 337
Book Description
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.
Author: Andreas Holzinger Publisher: Springer Nature ISBN: 3030504026 Category : Computers Languages : en Pages : 351
Book Description
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.
Author: Stanley Cohen Publisher: Elsevier Health Sciences ISBN: 0323675379 Category : Medical Languages : en Pages : 290
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.
Author: Publisher: BoD – Books on Demand ISBN: 1789840171 Category : Medical Languages : en Pages : 142
Book Description
Artificial intelligence (AI) is taking on an increasingly important role in our society today. In the early days, machines fulfilled only manual activities. Nowadays, these machines extend their capabilities to cognitive tasks as well. And now AI is poised to make a huge contribution to medical and biological applications. From medical equipment to diagnosing and predicting disease to image and video processing, among others, AI has proven to be an area with great potential. The ability of AI to make informed decisions, learn and perceive the environment, and predict certain behavior, among its many other skills, makes this application of paramount importance in today's world. This book discusses and examines AI applications in medicine and biology as well as challenges and opportunities in this fascinating area.
Author: Jyotir Moy Chatterjee Publisher: Springer Nature ISBN: 9819903696 Category : Medical Languages : en Pages : 202
Book Description
This book comprehensively reviews the potential of Artificial Intelligence (AI) in biomedical research and healthcare, with a major emphasis on virology. The initial chapter presents the applications of machine learning methods for structured data, such as the classical support vector machine and neural network, modern deep learning, and natural language processing for unstructured data in biomedical research and healthcare. The subsequent chapters explore the applications of AI in tackling COVID-19, analysis of the pandemic, viral infection, disease spread, and control. The book further identifies the potential applications of machine learning in the field of virology with a focus on the key aspects of infection: diagnosis, transmission, response to treatment, and resistance. The book also discusses progress and challenges in developing viral vaccines and examines the application of viruses in translational research and human healthcare. Furthermore, the book covers the applications of artificial intelligence-mediated diagnosis and the development of drugs to treat the disease. Towards the end, the book summarizes the ethical and legal challenges posed by AI in healthcare and biomedical research. This book is an invaluable source for researchers, medical and industry practitioners, academicians, and students exploring the applications of AI in biomedical research and healthcare.
Author: Deepshikha Agarwal Publisher: CRC Press ISBN: 1000906000 Category : Computers Languages : en Pages : 362
Book Description
This reference text presents the usage of artificial intelligence in healthcare and discusses the challenges and solutions of using advanced techniques like wearable technologies and image processing in the sector. Features: Focuses on the use of artificial intelligence (AI) in healthcare with issues, applications, and prospects Presents the application of artificial intelligence in medical imaging, fractionalization of early lung tumour detection using a low intricacy approach, etc Discusses an artificial intelligence perspective on wearable technology Analyses cardiac dynamics and assessment of arrhythmia by classifying heartbeat using electrocardiogram (ECG) Elaborates machine learning models for early diagnosis of depressive mental affliction This book serves as a reference for students and researchers analyzing healthcare data. It can also be used by graduate and post graduate students as an elective course.
Author: Sandeep Reddy Publisher: CRC Press ISBN: 1000216861 Category : Business & Economics Languages : en Pages : 287
Book Description
The rediscovery of the potential of artificial intelligence (AI) to improve healthcare delivery and patient outcomes has led to an increasing application of AI techniques such as deep learning, computer vision, natural language processing, and robotics in the healthcare domain. Many governments and health authorities have prioritized the application of AI in the delivery of healthcare. Also, technological giants and leading universities have established teams dedicated to the application of AI in medicine. These trends will mean an expanded role for AI in the provision of healthcare. Yet, there is an incomplete understanding of what AI is and its potential for use in healthcare. This book discusses the different types of AI applicable to healthcare and their application in medicine, population health, genomics, healthcare administration, and delivery. Readers, especially healthcare professionals and managers, will find the book useful to understand the different types of AI and how they are relevant to healthcare delivery. The book provides examples of AI being applied in medicine, population health, genomics, healthcare administration, and delivery and how they can commence applying AI in their health services. Researchers and technology professionals will also find the book useful to note current trends in the application of AI in healthcare and initiate their own projects to enable the application of AI in healthcare/medical domains.
Author: Ilias Maglogiannis Publisher: Springer Science & Business Media ISBN: 0387342230 Category : Computers Languages : en Pages : 761
Book Description
Artificial Intelligence applications build on a rich and proven theoretical background to provide solutions to a wide range of real life problems. The ever expanding abundance of information and computing power enables researchers and users to tackle higly interesting issues for the first time, such as applications providing personalized access and interactivity to multimodal information based on preferences and semantic concepts or human-machine interface systems utilizing information on the affective state of the user. The purpose of the 3rd IFIP Conference on Artificial Intelligence Applications and Innovations (AIAI) is to bring together researchers, engineers, and practitioners interested in the technical advances and business and industrial applications of intelligent systems. AIAI 2006 is focused on providing insights on how AI can be implemented in real world applications.
Author: Stanley Cohen Publisher: Elsevier ISBN: 032395832X Category : Science Languages : en Pages : 0
Book Description
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. Discusses the evolution of machine learning in the field to provide a foundational background Addresses challenges in the development, deployment and regulation of AI in anatomic pathology Includes information on generative deep learning in digital pathology workflows Provides current tools and future perspectives
Author: Abdulhamit Subasi Publisher: Academic Press ISBN: 0443184518 Category : Science Languages : en Pages : 381
Book Description
Applications of Artificial Intelligence in Medical Imaging provides the description of various biomedical image analysis in disease detection using AI that can be used to incorporate knowledge obtained from different medical imaging devices such as CT, X-ray, PET and ultrasound. The book discusses the use of AI for detection of several cancer types, including brain tumor, breast, pancreatic, rectal, lung colon, and skin. In addition, it explains how AI and deep learning techniques can be used to diagnose Alzheimer's, Parkinson's, COVID-19 and mental conditions. This is a valuable resource for clinicians, researchers and healthcare professionals who are interested in learning more about AI and its impact in medical/biomedical image analysis. Discusses new deep learning algorithms for image analysis and how they are used for medical images Provides several examples for each imaging technique, along with their application areas so that readers can rely on them as a clinical decision support system Describes how new AI tools may contribute significantly to the successful enhancement of a single patient's clinical knowledge to improve treatment outcomes
Author: Ralf Huss
Author: Ralf Huss
Author: Andreas Holzinger
Author: Stanley Cohen
Author: 
Author: Jyotir Moy Chatterjee
Author: Deepshikha Agarwal
Author: Sandeep Reddy
Author: Ilias Maglogiannis
Author: Stanley Cohen
Author: Abdulhamit Subasi