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.

Artificial Intelligence and Machine Learning for Digital Pathology

Artificial Intelligence and Machine Learning for Digital Pathology
Author: Andreas Holzinger,Randy Goebel,Michael Mengel,Heimo Müller
Publsiher: Springer Nature
Total Pages: 341
Release: 2020-06-24
ISBN 10: 3030504026
ISBN 13: 9783030504021
Language: EN, FR, DE, ES & NL

Artificial Intelligence and Machine Learning for Digital Pathology Book Review:

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

Artificial Intelligence and Deep Learning in Pathology
Author: Stanley Cohen
Publsiher: Elsevier
Total Pages: 250
Release: 2020-06
ISBN 10: 9780323675383
ISBN 13: 0323675387
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.

Digital Pathology

Digital Pathology
Author: Liron Pantanowitz,Anil V. Parwani
Publsiher: Unknown
Total Pages: 304
Release: 2017
ISBN 10: 9780891896104
ISBN 13: 0891896104
Language: EN, FR, DE, ES & NL

Digital Pathology Book Review:

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.

Whole Slide Imaging

Whole Slide Imaging
Author: Anil V. Parwani
Publsiher: Springer Nature
Total Pages: 242
Release: 2021-10-29
ISBN 10: 3030833321
ISBN 13: 9783030833329
Language: EN, FR, DE, ES & NL

Whole Slide Imaging Book Review:

This book provides up-to-date and practical knowledge in all aspects of whole slide imaging (WSI) by experts in the field. This includes a historical perspective on the evolution of this technology, technical aspects of making a great whole slide image, the various applications of whole slide imaging and future applications using WSI for computer-aided diagnosis The goal is to provide practical knowledge and address knowledge gaps in this emerging field. This book is unique because it addresses an emerging area in pathology for which currently there is only limited information about the practical aspects of deploying this technology. For example, there are no established selection criteria for choosing new scanners and a knowledge base with the key information. The authors of the various chapters have years of real-world experience in selecting and implementing WSI solutions in various aspects of pathology practice. This text also discusses practical tips and pearls to address the selection of a WSI vendor, technology details, implementing this technology and provide an overview of its everyday uses in all areas of pathology. Chapters include important information on how to integrate digital slides with laboratory information system and how to streamline the “digital workflow” with the intent of saving time, saving money, reducing errors, improving efficiency and accuracy, and ultimately benefiting patient outcomes. Whole Slide Imaging: Current Applications and Future Directions is designed to present a comprehensive and state-of the-art approach to WSI within the broad area of digital pathology. It aims to give the readers a look at WSI with a deeper lens and also envision the future of pathology imaging as it pertains to WSI and associated digital innovations.

Medical Imaging

Medical Imaging
Author: K.C. Santosh,Sameer Antani,DS Guru,Nilanjan Dey
Publsiher: CRC Press
Total Pages: 238
Release: 2019-08-20
ISBN 10: 0429642490
ISBN 13: 9780429642494
Language: EN, FR, DE, ES & NL

Medical Imaging Book Review:

The book discusses varied topics pertaining to advanced or up-to-date techniques in medical imaging using artificial intelligence (AI), image recognition (IR) and machine learning (ML) algorithms/techniques. Further, coverage includes analysis of chest radiographs (chest x-rays) via stacked generalization models, TB type detection using slice separation approach, brain tumor image segmentation via deep learning, mammogram mass separation, epileptic seizures, breast ultrasound images, knee joint x-ray images, bone fracture detection and labeling, and diabetic retinopathy. It also reviews 3D imaging in biomedical applications and pathological medical imaging.

Deep Medicine

Deep Medicine
Author: Eric Topol
Publsiher: Basic Books
Total Pages: 400
Release: 2019-03-12
ISBN 10: 1541644646
ISBN 13: 9781541644649
Language: EN, FR, DE, ES & NL

Deep Medicine Book Review:

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.

Machine Learning and the Internet of Medical Things in Healthcare

Machine Learning and the Internet of Medical Things in Healthcare
Author: Krishna Kant Singh,Mohamed Elhoseny,Akansha Singh,Ahmed A. Elngar
Publsiher: Academic Press
Total Pages: 290
Release: 2021-04-26
ISBN 10: 012823217X
ISBN 13: 9780128232170
Language: EN, FR, DE, ES & NL

Machine Learning and the Internet of Medical Things in Healthcare Book Review:

Machine Learning and the Internet of Medical Things in Healthcare discusses the applications and challenges of machine learning for healthcare applications. The book provides a platform for presenting machine learning-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes machine learning techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers worldwide. The book includes deep feed forward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology. It also presents the concepts of the Internet of Things, the set of technologies that develops traditional devices into smart devices. Finally, the book offers research perspectives, covering the convergence of machine learning and IoT. It also presents the application of these technologies in the development of healthcare frameworks. Provides an introduction to the Internet of Medical Things through the principles and applications of machine learning Explains the functions and applications of machine learning in various applications such as ultrasound imaging, biomedical signal processing, robotics, and biomechatronics Includes coverage of the evolution of healthcare applications with machine learning, including Clinical Decision Support Systems, artificial intelligence in biomedical engineering, and AI-enabled connected health informatics, supported by real-world case studies

Histology for Pathologists

Histology for Pathologists
Author: Stacey E. Mills
Publsiher: Lippincott Williams & Wilkins
Total Pages: 1328
Release: 2012-07-16
ISBN 10: 1451177801
ISBN 13: 9781451177800
Language: EN, FR, DE, ES & NL

Histology for Pathologists Book Review:

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.

Liquid Biopsy

Liquid Biopsy
Author: Ilze Strumfa,Janis Gardovskis
Publsiher: BoD – Books on Demand
Total Pages: 158
Release: 2019-07-10
ISBN 10: 183881129X
ISBN 13: 9781838811297
Language: EN, FR, DE, ES & NL

Liquid Biopsy Book Review:

Reliable diagnosis is the cornerstone, starting point, and prerequisite of successful treatment. Therefore, development of innovative diagnostic technologies represents a hot topic in medical research. Liquid biopsy is a novel, minimally invasive laboratory evaluation concept for diagnostic, prognostic, and predictive testing, as well as dynamic monitoring of treatment or disease course. To achieve these goals, a multitude of specific, targeted tests can be performed to detect free nucleic acids, exosomes, microRNAs, tumor-educated platelets, and whole cells of tumor or fetal origin in different biological fluids, including blood, urine, cerebrospinal fluid, and others. Although tissue biopsy has long been considered the gold standard of diagnostics, especially regarding malignant tumors, liquid biopsy has the advantages of a non-invasive approach and thus low risk of complications. It is technically feasible even in serious general status or if tumors or metastases are not easily accessible using conventional tissue biopsy. The testing is fast, exact, and can be repeated to ensure real-time follow-up. In contrast to classic tumor markers, liquid biopsy is distinguished by high specificity at genomic, proteomic, and cellular levels. It is expected to equal and exceed the diagnostic value of tissue biopsy. The field of liquid biopsies is developing rapidly regarding the selection of targets, technological improvements, and quality assessment. This book, written by a global team of recognized scientists, comprises state-of-the-art reviews on the current knowledge and advances in the technologies and software for liquid biopsy. Examples of practical application of liquid biopsy to evaluate thyroid cancer, multiple myeloma, etc. are discussed as well. The book is intended to serve as a reference for scientists and clinicians interested in the development and practical implementation of liquid biopsy.

Emerging Trends in ICT for Sustainable Development

Emerging Trends in ICT for Sustainable Development
Author: Mohamed Ben Ahmed,Sehl Mellouli,Luis Braganca,Boudhir Anouar Abdelhakim,Kwintiana Ane Bernadetta
Publsiher: Springer Nature
Total Pages: 407
Release: 2021-01-23
ISBN 10: 3030534405
ISBN 13: 9783030534400
Language: EN, FR, DE, ES & NL

Emerging Trends in ICT for Sustainable Development Book Review:

This book features original research and recent advances in ICT fields related to sustainable development. Based the International Conference on Networks, Intelligent systems, Computing & Environmental Informatics for Sustainable Development, held in Marrakech in April 2020, it features peer-reviewed chapters authored by prominent researchers from around the globe. As such it is an invaluable resource for courses in computer science, electrical engineering and urban sciences for sustainable development. This book covered topics including • Green Networks • Artificial Intelligence for Sustainability• Environment Informatics• Computing Technologies

Artificial Intelligence in Medicine

Artificial Intelligence in Medicine
Author: Allan Tucker,Pedro Henriques Abreu,Jaime Cardoso,Pedro Pereira Rodrigues,David Riaño
Publsiher: Springer Nature
Total Pages: 505
Release: 2021-06-08
ISBN 10: 303077211X
ISBN 13: 9783030772116
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Medicine Book Review:

This book constitutes the refereed proceedings of the 19th International Conference on Artificial Intelligence in Medicine, AIME 2021, held as a virtual event, in June 2021. The 28 full papers presented together with 30 short papers were selected from 138 submissions. The papers are grouped in topical sections on image analysis; predictive modelling; temporal data analysis; unsupervised learning; planning and decision support; deep learning; natural language processing; and knowledge representation and rule mining.

Natural Language Processing in Action

Natural Language Processing in Action
Author: Hannes Hapke,Cole Howard,Hobson Lane
Publsiher: Simon and Schuster
Total Pages: 544
Release: 2019-03-16
ISBN 10: 1638356890
ISBN 13: 9781638356899
Language: EN, FR, DE, ES & NL

Natural Language Processing in Action Book Review:

Summary Natural Language Processing in Action is your guide to creating machines that understand human language using the power of Python with its ecosystem of packages dedicated to NLP and AI. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Recent advances in deep learning empower applications to understand text and speech with extreme accuracy. The result? Chatbots that can imitate real people, meaningful resume-to-job matches, superb predictive search, and automatically generated document summaries—all at a low cost. New techniques, along with accessible tools like Keras and TensorFlow, make professional-quality NLP easier than ever before. About the Book Natural Language Processing in Action is your guide to building machines that can read and interpret human language. In it, you'll use readily available Python packages to capture the meaning in text and react accordingly. The book expands traditional NLP approaches to include neural networks, modern deep learning algorithms, and generative techniques as you tackle real-world problems like extracting dates and names, composing text, and answering free-form questions. What's inside Some sentences in this book were written by NLP! Can you guess which ones? Working with Keras, TensorFlow, gensim, and scikit-learn Rule-based and data-based NLP Scalable pipelines About the Reader This book requires a basic understanding of deep learning and intermediate Python skills. About the Author Hobson Lane, Cole Howard, and Hannes Max Hapke are experienced NLP engineers who use these techniques in production. Table of Contents PART 1 - WORDY MACHINES Packets of thought (NLP overview) Build your vocabulary (word tokenization) Math with words (TF-IDF vectors) Finding meaning in word counts (semantic analysis) PART 2 - DEEPER LEARNING (NEURAL NETWORKS) Baby steps with neural networks (perceptrons and backpropagation) Reasoning with word vectors (Word2vec) Getting words in order with convolutional neural networks (CNNs) Loopy (recurrent) neural networks (RNNs) Improving retention with long short-term memory networks Sequence-to-sequence models and attention PART 3 - GETTING REAL (REAL-WORLD NLP CHALLENGES) Information extraction (named entity extraction and question answering) Getting chatty (dialog engines) Scaling up (optimization, parallelization, and batch processing)

Artificial Intelligence in Healthcare

Artificial Intelligence in Healthcare
Author: Adam Bohr,Kaveh Memarzadeh
Publsiher: Academic Press
Total Pages: 378
Release: 2020-06-21
ISBN 10: 0128184396
ISBN 13: 9780128184394
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Healthcare Book Review:

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 in Medicine

Artificial Intelligence in Medicine
Author: David Riaño,Szymon Wilk,Annette ten Teije
Publsiher: Springer
Total Pages: 429
Release: 2019-06-19
ISBN 10: 303021642X
ISBN 13: 9783030216429
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Medicine Book Review:

This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.

Transplant Pathology

Transplant Pathology
Author: Peter C. Kolbeck,Bruce M. McManus,Rodney S. Markin,Maria R. Costanzo-Nordin
Publsiher: Amer Society of Clinical
Total Pages: 327
Release: 1994
ISBN 10: 1928374650XXX
ISBN 13: UOM:39015032303862
Language: EN, FR, DE, ES & NL

Transplant Pathology Book Review:

Digital Pathology

Digital Pathology
Author: Constantino Carlos Reyes-Aldasoro,Andrew Janowczyk,Mitko Veta,Peter Bankhead,Korsuk Sirinukunwattana
Publsiher: Springer
Total Pages: 192
Release: 2019-07-03
ISBN 10: 9783030239367
ISBN 13: 3030239365
Language: EN, FR, DE, ES & NL

Digital Pathology Book Review:

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.

Machine Learning in Dentistry

Machine Learning in Dentistry
Author: Ching-Chang Ko,Dinggang Shen,Li Wang
Publsiher: Springer Nature
Total Pages: 188
Release: 2021-07-24
ISBN 10: 3030718816
ISBN 13: 9783030718817
Language: EN, FR, DE, ES & NL

Machine Learning in Dentistry Book Review:

This book reviews all aspects of the use of machine learning in contemporary dentistry, clearly explaining its significance for dental imaging, oral diagnosis and treatment, dental designs, and dental research. Machine learning is an emerging field of artificial intelligence research and practice in which computer agents are employed to improve perception, cognition, and action based on their ability to “learn”, for example through use of big data techniques. Its application within dentistry is designed to promote personalized and precision patient care, with enhancement of diagnosis and treatment planning. In this book, readers will find up-to-date information on different machine learning tools and their applicability in various dental specialties. The selected examples amply illustrate the opportunities to employ a machine learning approach within dentistry while also serving to highlight the associated challenges. Machine Learning in Dentistry will be of value for all dental practitioners and researchers who wish to learn more about the potential benefits of using machine learning techniques in their work.

Machine Learning in Cardiovascular Medicine

Machine Learning in Cardiovascular Medicine
Author: Subhi J. Al'Aref,Gurpreet Singh,Lohendran Baskaran,Dimitri Metaxas
Publsiher: Academic Press
Total Pages: 454
Release: 2020-11-20
ISBN 10: 0128202742
ISBN 13: 9780128202746
Language: EN, FR, DE, ES & NL

Machine Learning in Cardiovascular Medicine Book Review:

Machine Learning in Cardiovascular Medicine addresses the ever-expanding applications of artificial intelligence (AI), specifically machine learning (ML), in healthcare and within cardiovascular medicine. The book focuses on emphasizing ML for biomedical applications and provides a comprehensive summary of the past and present of AI, basics of ML, and clinical applications of ML within cardiovascular medicine for predictive analytics and precision medicine. It helps readers understand how ML works along with its limitations and strengths, such that they can could harness its computational power to streamline workflow and improve patient care. It is suitable for both clinicians and engineers; providing a template for clinicians to understand areas of application of machine learning within cardiovascular research; and assist computer scientists and engineers in evaluating current and future impact of machine learning on cardiovascular medicine. Provides an overview of machine learning, both for a clinical and engineering audience Summarize recent advances in both cardiovascular medicine and artificial intelligence Discusses the advantages of using machine learning for outcomes research and image processing Addresses the ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach

Artificial Intelligence in Ophthalmology

Artificial Intelligence in Ophthalmology
Author: Andrzej Grzybowski
Publsiher: Springer
Total Pages: 286
Release: 2021-10-28
ISBN 10: 9783030786007
ISBN 13: 3030786005
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Ophthalmology Book Review:

This book provides a wide-ranging overview of artificial intelligence (AI), machine learning (ML) and deep learning (DL) algorithms in ophthalmology. Expertly written chapters examine AI in age-related macular degeneration, glaucoma, retinopathy of prematurity and diabetic retinopathy screening. AI perspectives, systems and limitations are all carefully assessed throughout the book as well as the technical aspects of DL systems for retinal diseases including the application of Google DeepMind, the Singapore algorithm, and the Johns Hopkins algorithm. Artificial Intelligence in Ophthalmology meets the need for a resource that reviews the benefits and pitfalls of AI, ML and DL in ophthalmology. Ophthalmologists, optometrists, eye-care workers, neurologists, cardiologists, internal medicine specialists, AI engineers and IT specialists with an interest in how AI can help with early diagnosis and monitoring treatment in ophthalmic patients will find this book to be an indispensable guide to an evolving area of healthcare technology.