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Artificial Intelligence and Deep Learning in Pathology E Book

Artificial Intelligence and Deep Learning in Pathology E Book
  • Author : Stanley Cohen
  • Publsiher : Elsevier Health Sciences
  • Release : 02 June 2020
  • ISBN : 0323675379
  • Pages : 288 pages
  • Rating : 4/5 from 21 ratings
GET THIS BOOKArtificial Intelligence and Deep Learning in Pathology E Book

Summary:
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 Deep Learning in Pathology E-Book

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

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



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


Artificial Intelligence in Medicine

Artificial Intelligence in Medicine
  • Author : Lei Xing,Maryellen L. Giger,James K Min
  • Publisher : Academic Press
  • Release : 16 September 2020
GET THIS BOOKArtificial Intelligence in Medicine

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


Deep Learning for Medical Image Analysis

Deep Learning for Medical Image Analysis
  • Author : S. Kevin Zhou,Hayit Greenspan,Dinggang Shen
  • Publisher : Academic Press
  • Release : 18 January 2017
GET THIS BOOKDeep Learning for Medical Image Analysis

Deep learning is providing exciting solutions for medical image analysis problems and is seen as a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component have been applied to medical image detection, segmentation and registration, and computer-aided analysis, using a wide variety of application areas. Deep Learning for Medical Image Analysis is a great


Artificial Intelligence In Medicine

Artificial Intelligence In Medicine
  • Author : Peter Szolovits
  • Publisher : Routledge
  • Release : 13 March 2019
GET THIS BOOKArtificial Intelligence In Medicine

This book introduces the field of artificial intelligence in medicine, a new research area that combines sophisticated representational and computing techniques with the insights of expert physicians to produce tools for improving health care. An introductory chapter describes the historical and technical foundations of the work and provides an overview of the current state of the art and research directions. The authors then describe four prototype computer programs that tackle difficult clinical problems in a manner similar to that of


Artificial Intelligence in Medical Imaging

Artificial Intelligence in Medical Imaging
  • Author : Lia Morra,Silvia Delsanto,Loredana Correale
  • Publisher : CRC Press
  • Release : 25 November 2019
GET THIS BOOKArtificial Intelligence in Medical Imaging

This book, written by authors with more than a decade of experience in the design and development of artificial intelligence (AI) systems in medical imaging, will guide readers in the understanding of one of the most exciting fields today. After an introductory description of classical machine learning techniques, the fundamentals of deep learning are explained in a simple yet comprehensive manner. The book then proceeds with a historical perspective of how medical AI developed in time, detailing which applications triumphed


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


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



Artificial Intelligence in Medicine

Artificial Intelligence in Medicine
  • Author : David Riaño,Szymon Wilk,Annette ten Teije
  • Publisher : Springer
  • Release : 19 June 2019
GET THIS BOOKArtificial Intelligence in Medicine

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.


Digital Pathology

Digital Pathology
  • Author : Liron Pantanowitz,Anil V. Parwani
  • Publisher : Anonim
  • Release : 01 March 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


Deep Learning for the Life Sciences

Deep Learning for the Life Sciences
  • Author : Bharath Ramsundar,Peter Eastman,Patrick Walters,Vijay Pande
  • Publisher : O'Reilly Media
  • Release : 10 April 2019
GET THIS BOOKDeep Learning for the Life Sciences

Deep learning has already achieved remarkable results in many fields. Now it’s making waves throughout the sciences broadly and the life sciences in particular. This practical book teaches developers and scientists how to use deep learning for genomics, chemistry, biophysics, microscopy, medical analysis, and other fields. Ideal for practicing developers and scientists ready to apply their skills to scientific applications such as biology, genetics, and drug discovery, this book introduces several deep network primitives. You’ll follow a case


Medical Imaging

Medical Imaging
  • Author : K.C. Santosh,Sameer Antani,DS Guru,Nilanjan Dey
  • Publisher : CRC Press
  • Release : 20 August 2019
GET THIS BOOKMedical Imaging

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


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.