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Artificial Intelligence and Deep Learning in Pathology

Artificial Intelligence and Deep Learning in Pathology
  • 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

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

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 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 : 24 June 2020
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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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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Digital Pathology

Digital Pathology
  • Author : Liron Pantanowitz,Anil V. Parwani
  • Publisher : Anonim
  • Release : 17 May 2022
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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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
  • Publisher : Academic Press
  • Release : 26 April 2021
GET THIS BOOKMachine Learning and the Internet of Medical Things in Healthcare

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

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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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Liquid Biopsy

Liquid Biopsy
  • Author : Ilze Strumfa,Janis Gardovskis
  • Publisher : BoD – Books on Demand
  • Release : 10 July 2019
GET THIS BOOKLiquid Biopsy

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

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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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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

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Histology for Pathologists

Histology for Pathologists
  • Author : Stacey E. Mills
  • Publisher : Lippincott Williams & Wilkins
  • Release : 16 July 2012
GET THIS BOOKHistology for Pathologists

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,

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Machine Learning for Health Informatics

Machine Learning for Health Informatics
  • Author : Andreas Holzinger
  • Publisher : Springer
  • Release : 09 December 2016
GET THIS BOOKMachine Learning for Health Informatics

Machine learning (ML) is the fastest growing field in computer science, and Health Informatics (HI) is amongst the greatest application challenges, providing future benefits in improved medical diagnoses, disease analyses, and pharmaceutical development. However, successful ML for HI needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. Tackling complex challenges needs both disciplinary excellence and cross-disciplinary networking without any boundaries. Following the HCI-KDD approach, in combining the best of two worlds,

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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
  • Publisher : Springer Nature
  • Release : 23 January 2021
GET THIS BOOKEmerging Trends in ICT for Sustainable Development

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

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Artificial Intelligence in Medicine

Artificial Intelligence in Medicine
  • Author : Lei Xing,Maryellen L. Giger,James K. Min
  • Publisher : Academic Press
  • Release : 03 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

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Bioinformatics Basics

Bioinformatics Basics
  • Author : Lukas K. Buehler,Hooman H. Rashidi
  • Publisher : CRC Press
  • Release : 23 June 2005
GET THIS BOOKBioinformatics Basics

Every researcher in genomics and proteomics now has access to public domain databases containing literally billions of data entries. However, without the right analytical tools, and an understanding of the biological significance of the data, cataloging and interpreting the molecular evolutionary processes buried in those databases is difficult, if not impossible. The first editon of Bioinformatics Basics: Applications in Biological Science and Medicine answered the scientific community’s need to learn about the bioinformatic tools available to them. That the

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Machine Learning in Cardiovascular Medicine

Machine Learning in Cardiovascular Medicine
  • Author : Subhi J. Al'Aref,Gurpreet Singh,Lohendran Baskaran,Dimitri Metaxas
  • Publisher : Academic Press
  • Release : 20 November 2020
GET THIS BOOKMachine Learning in Cardiovascular Medicine

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

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