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Synopsis
Computational pathology is an emerging field that integrates digital pathology, artificial intelligence (AI), machine learning (ML), and image analysis techniques to enhance the diagnosis, grading, risk assessment, and management of oral potentially malignant disorders (OPMDs). OPMDs, including oral leukoplakia, oral erythroplakia, oral submucous fibrosis, and oral lichen planus, possess varying risks of malignant transformation into oral squamous cell carcinoma (OSCC). Accurate prediction of this transformation remains a significant challenge in conventional histopathology due to interobserver variability and subjective interpretation. Computational pathology represents a transformative approach in the evaluation of OPMDs. By providing objective, quantitative, and reproducible analyses, it has the potential to improve diagnostic accuracy, predict malignant transformation more effectively, and facilitate personalized patient management, ultimately contributing to better outcomes in oral cancer prevention and early detection.
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COMPUTATIONAL PATHOLOGY IN ORAL POTENTIALLY MALIGNANT DISORDERS
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LAP LAMBERT Academic Publishing, 2026
ISBN 10: 6630091620
ISBN 13: 9786630091625
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COMPUTATIONAL PATHOLOGY IN ORAL POTENTIALLY MALIGNANT DISORDERS
Published by
LAP LAMBERT Academic Publishing, 2026
ISBN 10: 6630091620
ISBN 13: 9786630091625
New
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # L2-9786630091625
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Computational Pathology in Oral Potentially Malignant Disorders (Paperback)
Published by
LAP Lambert Academic Publishing, 2026
ISBN 10: 6630091620
ISBN 13: 9786630091625
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Paperback. Condition: new. Paperback. Computational pathology is an emerging field that integrates digital pathology, artificial intelligence (AI), machine learning (ML), and image analysis techniques to enhance the diagnosis, grading, risk assessment, and management of oral potentially malignant disorders (OPMDs). OPMDs, including oral leukoplakia, oral erythroplakia, oral submucous fibrosis, and oral lichen planus, possess varying risks of malignant transformation into oral squamous cell carcinoma (OSCC). Accurate prediction of this transformation remains a significant challenge in conventional histopathology due to interobserver variability and subjective interpretation. Computational pathology represents a transformative approach in the evaluation of OPMDs. By providing objective, quantitative, and reproducible analyses, it has the potential to improve diagnostic accuracy, predict malignant transformation more effectively, and facilitate personalized patient management, ultimately contributing to better outcomes in oral cancer prevention and early detection. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9786630091625
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COMPUTATIONAL PATHOLOGY IN ORAL POTENTIALLY MALIGNANT DISORDERS
Published by
LAP LAMBERT Academic Publishing Jun 2026, 2026
ISBN 10: 6630091620
ISBN 13: 9786630091625
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 128 pp. Englisch. Seller Inventory # 9786630091625
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Computational Pathology in Oral Potentially Malignant Disorders (Paperback)
Published by
LAP Lambert Academic Publishing, 2026
ISBN 10: 6630091620
ISBN 13: 9786630091625
New
Paperback
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Paperback. Condition: new. Paperback. Computational pathology is an emerging field that integrates digital pathology, artificial intelligence (AI), machine learning (ML), and image analysis techniques to enhance the diagnosis, grading, risk assessment, and management of oral potentially malignant disorders (OPMDs). OPMDs, including oral leukoplakia, oral erythroplakia, oral submucous fibrosis, and oral lichen planus, possess varying risks of malignant transformation into oral squamous cell carcinoma (OSCC). Accurate prediction of this transformation remains a significant challenge in conventional histopathology due to interobserver variability and subjective interpretation. Computational pathology represents a transformative approach in the evaluation of OPMDs. By providing objective, quantitative, and reproducible analyses, it has the potential to improve diagnostic accuracy, predict malignant transformation more effectively, and facilitate personalized patient management, ultimately contributing to better outcomes in oral cancer prevention and early detection. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9786630091625
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COMPUTATIONAL PATHOLOGY IN ORAL POTENTIALLY MALIGNANT DISORDERS
Published by
LAP LAMBERT Academic Publishing, 2026
ISBN 10: 6630091620
ISBN 13: 9786630091625
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Taschenbuch. Condition: Neu. COMPUTATIONAL PATHOLOGY IN ORAL POTENTIALLY MALIGNANT DISORDERS | Smitha Kuttappan (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786630091625 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. Seller Inventory # 135816239
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COMPUTATIONAL PATHOLOGY IN ORAL POTENTIALLY MALIGNANT DISORDERS
Published by
LAP LAMBERT Academic Publishing Jun 2026, 2026
ISBN 10: 6630091620
ISBN 13: 9786630091625
New
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware 128 pp. Englisch. Seller Inventory # 9786630091625
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COMPUTATIONAL PATHOLOGY IN ORAL POTENTIALLY MALIGNANT DISORDERS
Published by
LAP LAMBERT Academic Publishing, 2026
ISBN 10: 6630091620
ISBN 13: 9786630091625
New
Taschenbuch
Seller: AHA-BUCH GmbH, Einbeck, Germany
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Computational pathology is an emerging field that integrates digital pathology, artificial intelligence (AI), machine learning (ML), and image analysis techniques to enhance the diagnosis, grading, risk assessment, and management of oral potentially malignant disorders (OPMDs). OPMDs, including oral leukoplakia, oral erythroplakia, oral submucous fibrosis, and oral lichen planus, possess varying risks of malignant transformation into oral squamous cell carcinoma (OSCC). Accurate prediction of this transformation remains a significant challenge in conventional histopathology due to interobserver variability and subjective interpretation. Computational pathology represents a transformative approach in the evaluation of OPMDs. By providing objective, quantitative, and reproducible analyses, it has the potential to improve diagnostic accuracy, predict malignant transformation more effectively, and facilitate personalized patient management, ultimately contributing to better outcomes in oral cancer prevention and early detection. Seller Inventory # 9786630091625
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