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Artificial Intelligence and Deep Learning in Pathology

Artificial Intelligence and Deep Learning in Pathology
  • Author : Stanley Cohen
  • Publisher : Elsevier Health Sciences
  • Release : 02 June 2020
GET THIS BOOKArtificial Intelligence and Deep Learning in Pathology

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

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Artificial Intelligence and Deep Learning in Pathology

Artificial Intelligence and Deep Learning in Pathology
  • Author : Stanley Cohen
  • Publisher : Elsevier
  • Release : 01 June 2020
GET THIS BOOKArtificial Intelligence and Deep Learning in Pathology

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

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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
  • Publisher : Springer Nature
  • Release : 09 December 2021
GET THIS BOOKArtificial Intelligence and Machine Learning for Digital Pathology

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

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Digital Pathology

Digital Pathology
  • Author : Liron Pantanowitz,Anil V. Parwani
  • Publisher : Anonim
  • Release : 09 December 2021
GET THIS BOOKDigital Pathology

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

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Current and Future Application of Artificial Intelligence in Clinical Medicine

Current and Future Application of Artificial Intelligence in Clinical Medicine
  • Author : Jie Yang,Shigao Huang
  • Publisher : Bentham Science Publishers
  • Release : 01 June 2021
GET THIS BOOKCurrent and Future Application of Artificial Intelligence in Clinical Medicine

Current and Future Application of Artificial Intelligence in Clinical Medicine presents updates on the application of machine learning and deep learning techniques in medical procedures. . Chapters in the volume have been written by outstanding contributors from cancer and computer science institutes with the goal of providing updated knowledge to the reader. Topics covered in the book include 1) Artificial Intelligence (AI) applications in cancer diagnosis and therapy, 2) Updates in AI applications in the medical industry, 3) the use of AI in studying

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Deep Learning in Computational Mechanics

Deep Learning in Computational Mechanics
  • Author : Stefan Kollmannsberger
  • Publisher : Springer Nature
  • Release : 09 December 2021
GET THIS BOOKDeep Learning in Computational Mechanics

This book provides a first course on deep learning in computational mechanics. The book starts with a short introduction to machine learning's fundamental concepts before neural networks are explained thoroughly. It then provides an overview of current topics in physics and engineering, setting the stage for the book's main topics: physics-informed neural networks and the deep energy method. The idea of the book is to provide the basic concepts in a mathematically sound manner and yet to stay as simple

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Handbook of Deep Learning in Biomedical Engineering

Handbook of Deep Learning in Biomedical Engineering
  • Author : Valentina Emilia Balas,Brojo Kishore Mishra,Raghvendra Kumar
  • Publisher : Academic Press
  • Release : 23 November 2020
GET THIS BOOKHandbook of Deep Learning in Biomedical Engineering

Deep learning (DL) is a method of machine learning, running over artificial neural networks, that uses multiple layers to extract high-level features from large amounts of raw data. DL methods apply levels of learning to transform input data into more abstract and composite information. Handbook for Deep Learning in Biomedical Engineering: Techniques and Applications gives readers a complete overview of the essential concepts of DL and its applications in the field of biomedical engineering. DL has been rapidly developed in

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Digital Pathology

Digital Pathology
  • Author : Constantino Carlos Reyes-Aldasoro,Andrew Janowczyk,Mitko Veta,Peter Bankhead,Korsuk Sirinukunwattana
  • Publisher : Springer
  • Release : 03 July 2019
GET THIS BOOKDigital Pathology

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.

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Deep Medicine

Deep Medicine
  • Author : Eric Topol
  • Publisher : Basic Books
  • Release : 12 March 2019
GET THIS BOOKDeep Medicine

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

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Artificial Intelligence in Medical Imaging

Artificial Intelligence in Medical Imaging
  • Author : Erik R. Ranschaert,Sergey Morozov,Paul R. Algra
  • Publisher : Springer
  • Release : 29 January 2019
GET THIS BOOKArtificial Intelligence in Medical Imaging

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

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Artificial Intelligence Applications in Human Pathology

Artificial Intelligence Applications in Human Pathology
  • Author : Ralf Huss,Michael Grunkin
  • Publisher : Anonim
  • Release : 22 January 2022
GET THIS BOOKArtificial Intelligence Applications in Human Pathology

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

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Artificial Intelligence in Design ’96

Artificial Intelligence in Design ’96
  • Author : John S. Gero,Fay Sudweeks
  • Publisher : Springer Science & Business Media
  • Release : 06 December 2012
GET THIS BOOKArtificial Intelligence in Design ’96

Change is one of the most significant parameters in our society. Designers are amongst the primary change agents for any society. As a consequence design is an important research topic in engineering and architecture and related disciplines, since design is not only a means of change but is also one of the keystones to economic competitiveness and the fundamental precursor to manufacturing. The development of computational models founded on the artificial intelligence paradigm has provided an impetus for much of

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Deep Learning in Healthcare

Deep Learning in Healthcare
  • Author : Yen-Wei Chen,Lakhmi C. Jain
  • Publisher : Springer Nature
  • Release : 18 November 2019
GET THIS BOOKDeep Learning in Healthcare

This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diagnosis systems. Deep learning (DL) is one of the key techniques of artificial intelligence (AI) and today plays an important role in numerous academic and industrial areas. DL involves using a neural network with many layers (deep structure) between input and output,

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Deep Learning for Cancer Diagnosis

Deep Learning for Cancer Diagnosis
  • Author : Utku Kose,Jafar Alzubi
  • Publisher : Springer Nature
  • Release : 12 September 2020
GET THIS BOOKDeep Learning for Cancer Diagnosis

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

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