000 04601cam a22004818a 4500
001 000q0336
003 WSP
005 20240731095200.0
007 cr |nu|||unuuu
008 210814s2022 si ob 001 0 eng
010 _a 2021038679
040 _aWSPC
_beng
_cWSPC
015 _aGBC1I9901
_2bnb
016 7 _a020393743
_2Uk
020 _a9781800611399
_q(ebook)
020 _a1800611390
_q(ebook)
020 _z9781800611382
_q(hbk.)
020 _z1800611382
_q(hbk.)
035 _a(OCoLC)1264137354
042 _apcc
050 0 0 _aRB38
_b.A78 2022
072 7 _aSCI
_x102000
_2bisacsh
072 7 _aSCI
_x036000
_2bisacsh
072 7 _aSCI
_x008000
_2bisacsh
082 0 0 _a616.07/5
_223
049 _aMAIN
245 0 0 _aArtificial intelligence applications in human pathology
_h[electronic resource]/
_ceditors, Ralf Huss, Michael Grunkin.
260 _aSingapore :
_bWorld Scientific,
_c[2022]
300 _a1 online resource (336 p.).
504 _aIncludes bibliographical references and index.
505 0 _aForeword -- About the editors -- Introduction: integration of computational pathology and AI application into histopathology workflow -- Standardized tissue sampling for automated analysis and global trial success -- Light-sheet microscopy as a novel tool for virtual histology -- Stain quality management and biomarker analysis -- Measuring Ki-67 in breast cancer: past, present, and future -- Multiplex: from acquisition to analysis -- An introduction to deep learning in pathology -- AI-driven precision pathology: challenges and innovations in tissue biomarker analysis for diagnosis -- Tissue cartography for colorectal cancer -- Graph representation learning and explainability in breast cancer pathology: bridging the gap between AI and pathology practice -- AI-driven design of disease sensors: theoretical foundations -- Index.
520 _a"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 are faced with an increased workload both quantitatively (numbers of cases) and qualitatively (the amount of work per case, with increasing treatment options and the type of data delivered by pathologists also expected to become more fine-grained). AI will support and leverage mathematical tools and implement data-driven methods as a center for data interpretation in modern tissue diagnosis and pathology. Digital or computational pathology will also foster the training of future computational pathologists, those with both pathology and non-pathology backgrounds, who will eventually decide that AI-based pathology will serve as an indispensable hub for data-related research in a global health care system. Some of the specific topics explored within include an introduction to DL as applied to Pathology, Standardized Tissue Sampling for Automated Analysis, integrating Computational Pathology into Histopathology workflows. Readers will also find examples of specific techniques applied to specific diseases that will aid their research and treatments including but not limited to; Tissue Cartography for Colorectal Cancer, Ki-67 Measurements in Breast Cancer, and Light-Sheet Microscopy as applied to Virtual Histology. The key role for pathologists in tissue diagnostics will prevail and even expand through interdisciplinary work and the intuitive use of an advanced and interoperating (AI-supported) pathology workflow delivering novel and complex features that will serve the understanding of individual diseases and of course the patient"--
_cProvided by publisher.
538 _aMode of access: World Wide Web.
538 _aSystem requirements: Adobe Acrobat reader.
650 0 _aDiagnosis, Laboratory
_xData processing.
_9178284
650 0 _aArtificial intelligence
_xMedical applications.
_94809
650 0 _aPathology
_xTechnological innovations.
_9178285
655 0 _aElectronic books.
_93294
700 1 _aHuss, Ralf.
_9178286
700 1 _aGrunkin, Michael.
_9178287
856 4 0 _uhttps://www.worldscientific.com/worldscibooks/10.1142/q0336#t=toc
_zAccess to full text is restricted to subscribers.
942 _cEBK
999 _c97735
_d97735