Artificial Intelligence and Deep Learning in Pathology
- ISBN-10
- 0323675379
- ISBN-13
- 9780323675376
- Category
- Medical
- Pages
- 288
- Language
- English
- Published
- 2020-06-02
- Publisher
- Elsevier Health Sciences
- Author
- Stanley Cohen
Description
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.
Get the book
Other editions
Similar books
-
Artificial Intelligence and Machine Learning for Digital Pathology: State-of-the-Art and Future Challenges
By Andreas Holzinger, Randy Goebel, Michael MengelData 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.
-
Artificial Intelligence and Machine Learning for Digital Pathology: State-of-the-Art and Future Challenges
By Andreas Holzinger, Randy Goebel, Michael MengelData 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.
-
Histology for Pathologists
By Stacey E. Millshistologic artifacts that are usually encountered only in autopsy specimens of the CNS. ... McLendonRE, Bigner DD,Rosenblum M, etal.Russell & Rubinstein's Pathology of Tumors of the Nervous System. 7th ed.
-
Artificial Intelligence in Medical Imaging: Opportunities, Applications and Risks
By Erik R. Ranschaert, Sergey Morozov, Paul R. AlgraThis 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 ...
-
Digital Pathology
By Liron Pantanowitz, Anil V. ParwaniAn extraordinarily comprehensive and complete book for individuals with anything from minimal knowledge to deep, accomplished experience in digital pathology.
-
Artificial Intelligence in Ophthalmology
By Andrzej GrzybowskiThis book provides a wide-ranging overview of artificial intelligence (AI), machine learning (ML) and deep learning (DL) algorithms in ophthalmology.
-
Artificial Intelligence Applications in Human Pathology
By Ralf Huss, Michael GrunkinWith 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 ...
-
Medical Imaging: Artificial Intelligence, Image Recognition, and Machine Learning Techniques
By Nilanjan Dey, K.C. Santosh, Sameer AntaniThe 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.
-
Bioinformatics Basics: Applications in Biological Science and Medicine
By Lukas K. Buehler, Hooman H. RashidiEvery researcher in genomics and proteomics now has access to public domain databases containing literally billions of data entries.
-
Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again
By Eric TopolIn Deep Medicine, leading physician Eric Topol reveals how artificial intelligence can help.