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Artificial Intelligence and Deep Learning in Pathology

Artificial Intelligence and Deep Learning in Pathology
A Book

by Stanley Cohen

  • Publisher : Elsevier
  • Release : 2020-06
  • Pages : 250
  • ISBN : 9780323675383
  • Language : En, Es, Fr & De
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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
State-of-the-Art and Future Challenges

by Andreas Holzinger,Randy Goebel,Michael Mengel,Heimo Müller

  • Publisher : Springer
  • Release : 2020-06-21
  • Pages : 341
  • ISBN : 9783030504014
  • Language : En, Es, Fr & De
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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 E-Book

Artificial Intelligence and Deep Learning in Pathology E-Book
A Book

by Stanley Cohen

  • Publisher : Elsevier Health Sciences
  • Release : 2020-06-02
  • Pages : 288
  • ISBN : 0323675379
  • Language : En, Es, Fr & De
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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
State-of-the-Art and Future Challenges

by Andreas Holzinger

  • Publisher : Springer Nature
  • Release : 2021
  • Pages : 329
  • ISBN : 3030504026
  • Language : En, Es, Fr & De
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Deep Learning for Medical Image Analysis

Deep Learning for Medical Image Analysis
A Book

by S. Kevin Zhou,Hayit Greenspan,Dinggang Shen

  • Publisher : Academic Press
  • Release : 2017-01-18
  • Pages : 458
  • ISBN : 0128104090
  • Language : En, Es, Fr & De
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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 learning resource for academic and industry researchers in medical imaging analysis, and for graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Covers common research problems in medical image analysis and their challenges Describes deep learning methods and the theories behind approaches for medical image analysis Teaches how algorithms are applied to a broad range of application areas, including Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc. Includes a Foreword written by Nicholas Ayache

Computational Pathology and Ophthalmic Medical Image Analysis

Computational Pathology and Ophthalmic Medical Image Analysis
First International Workshop, COMPAY 2018, and 5th International Workshop, OMIA 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16 - 20, 2018, Proceedings

by Danail Stoyanov,Zeike Taylor,Francesco Ciompi,Yanwu Xu,Anne Martel,Lena Maier-Hein,Nasir Rajpoot,Jeroen van der Laak,Mitko Veta,Stephen McKenna,David Snead,Emanuele Trucco,Mona K. Garvin,Xin Jan Chen,Hrvoje Bogunovic

  • Publisher : Springer
  • Release : 2018-09-13
  • Pages : 347
  • ISBN : 3030009491
  • Language : En, Es, Fr & De
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This book constitutes the refereed joint proceedings of the First International Workshop on Computational Pathology, COMPAY 2018, and the 5th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018. The 19 full papers (out of 25 submissions) presented at COMPAY 2018 and the 21 full papers (out of 31 submissions) presented at OMIA 2018 were carefully reviewed and selected. The COMPAY papers focus on artificial intelligence and deep learning. The OMIA papers cover various topics in the field of ophthalmic image analysis.

Proceedings of the ... International Workshop on Machine Learning

Proceedings of the ... International Workshop on Machine Learning
A Book

by Anonim

  • Publisher : Unknown Publisher
  • Release : 1985
  • Pages : 329
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Deep Learning for Cancer Diagnosis

Deep Learning for Cancer Diagnosis
A Book

by Utku Kose

  • Publisher : Springer Nature
  • Release : 2021
  • Pages : 329
  • ISBN : 9811563217
  • Language : En, Es, Fr & De
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Artificial Intelligence in Medicine

Artificial Intelligence in Medicine
Technical Basis and Clinical Applications

by Lei Xing,Maryellen L. Giger,James K Min

  • Publisher : Academic Press
  • Release : 2020-09-16
  • Pages : 568
  • ISBN : 0128212586
  • Language : En, Es, Fr & De
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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 and healthcare delivery. Integrating AI within medicine has been met with both excitement and scepticism. By understanding how AI works, and developing an appreciation for both limitations and strengths, clinicians can harness its computational power to streamline workflow and improve patient care. It also provides the opportunity to improve upon research methodologies beyond what is currently available using traditional statistical approaches. On the other hand, computers scientists and data analysts can provide solutions, but often lack easy access to clinical insight that may help focus their efforts. This book provides vital background knowledge to help bring these two groups together, and to engage in more streamlined dialogue to yield productive collaborative solutions in the field of medicine. Provides history and overview of artificial intelligence, as narrated by pioneers in the field Discusses broad and deep background and updates on recent advances in both medicine and artificial intelligence that enabled the application of artificial intelligence Addresses the ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach

Medical Imaging

Medical Imaging
Artificial Intelligence, Image Recognition, and Machine Learning Techniques

by K.C. Santosh,Sameer Antani,DS Guru,Nilanjan Dey

  • Publisher : CRC Press
  • Release : 2019-08-20
  • Pages : 238
  • ISBN : 0429639325
  • Language : En, Es, Fr & De
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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.

Computational Pathology

Computational Pathology
A Machine Learning Approach

by Thomas J. Fuchs

  • Publisher : Unknown Publisher
  • Release : 2010
  • Pages : 329
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Veterinary Clinical Pathology

Veterinary Clinical Pathology
A Book

by Anonim

  • Publisher : Unknown Publisher
  • Release : 1998
  • Pages : 329
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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A Game-learning Machine

A Game-learning Machine
A Book

by Michael Gherrity

  • Publisher : Unknown Publisher
  • Release : 1993
  • Pages : 192
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Artificial Intelligence in Cancer

Artificial Intelligence in Cancer
Diagnostic to Tailored Treatment

by Smaranda Belciug

  • Publisher : Academic Press
  • Release : 2020-07-15
  • Pages : 318
  • ISBN : 0128202017
  • Language : En, Es, Fr & De
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Artificial Intelligence in Cancer: Diagnostic to Tailored Treatment provides theoretical concepts and practical techniques of AI and its applications in cancer management, building a roadmap on how to use AI in cancer at different stages of healthcare. It discusses topics such as the impactful role of AI during diagnosis and how it can support clinicians to make better decisions, AI tools to help pathologists identify exact types of cancer, how AI supports tumor profiling and can assist surgeons, and the gains in precision for oncologists using AI tools. Additionally, it provides information on AI used for survival and remission/recurrence analysis. The book is a valuable source for bioinformaticians, cancer researchers, oncologists, clinicians and members of the biomedical field who want to understand the promising field of AI applications in cancer management. Discusses over 20 real cancer examples, bringing state-of-the-art cancer cases in which AI was used to help the medical personnel Presents over 100 diagrams, making it easier to comprehend AI's results on a specific problem through visual resources Explains AI algorithms in a friendly manner, thus helping the reader implement or use them in a specific cancer case

Archives of Pathology & Laboratory Medicine

Archives of Pathology & Laboratory Medicine
A Book

by Anonim

  • Publisher : Unknown Publisher
  • Release : 1987
  • Pages : 329
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Towards Integrative Machine Learning and Knowledge Extraction

Towards Integrative Machine Learning and Knowledge Extraction
BIRS Workshop, Banff, AB, Canada, July 24-26, 2015, Revised Selected Papers

by Andreas Holzinger,Randy Goebel,Massimo Ferri,Vasile Palade

  • Publisher : Springer
  • Release : 2017-10-27
  • Pages : 207
  • ISBN : 3319697757
  • Language : En, Es, Fr & De
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The BIRS Workshop “Advances in Interactive Knowledge Discovery and Data Mining in Complex and Big Data Sets” (15w2181), held in July 2015 in Banff, Canada, was dedicated to stimulating a cross-domain integrative machine-learning approach and appraisal of “hot topics” toward tackling the grand challenge of reaching a level of useful and useable computational intelligence with a focus on real-world problems, such as in the health domain. This encompasses learning from prior data, extracting and discovering knowledge, generalizing the results, fighting the curse of dimensionality, and ultimately disentangling the underlying explanatory factors in complex data, i.e., to make sense of data within the context of the application domain. The workshop aimed to contribute advancements in promising novel areas such as at the intersection of machine learning and topological data analysis. History has shown that most often the overlapping areas at intersections of seemingly disparate fields are key for the stimulation of new insights and further advances. This is particularly true for the extremely broad field of machine learning.

Advances in Web Intelligence and Data Mining

Advances in Web Intelligence and Data Mining
A Book

by Mark Last,Piotr S. Szczepaniak,Zeev Volkovich,Abraham Kandel

  • Publisher : Springer
  • Release : 2006-05-23
  • Pages : 340
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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This book presents state-of-the-art developments in the area of computationally intelligent methods applied to various aspects and ways of Web exploration and Web mining. Some novel data mining algorithms that can lead to more effective and intelligent Web-based systems are also described. Scientists, engineers, and research students can expect to find many inspiring ideas in this volume.

Machine Learning for Systems Pathology

Machine Learning for Systems Pathology
A Book

by Wim Verleyen,University of St. Andrews. School of Biology

  • Publisher : Unknown Publisher
  • Release : 2013
  • Pages : 334
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Proceedings of the Twelfth Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Proceedings of the Twelfth Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Volume 12, 1990, Philadelphia, Pennsylvania, USA, November 1-4, 1990

by IEEE Engineering in Medicine and Biology Society. Annual Conference

  • Publisher : Unknown Publisher
  • Release : 1990
  • Pages : 2378
  • ISBN : 9780879425593
  • Language : En, Es, Fr & De
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IJCAI-03

IJCAI-03
Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence, Acapulco, Mexico, August 9-15, 2003

by International Joint Conferences on Artificial Intelligence,Mexican Society for Artificial Intelligence

  • Publisher : Ap Professional
  • Release : 2003
  • Pages : 1675
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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