ISBN: 9786630091625 - computational pathology in oral potentially malignant disorders (8 resultados)

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Paperback. Condición: 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.…

PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 128 pp. Englisch.

Paperback. Condición: 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.…

Taschenbuch. Condición: 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.…

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware 128 pp. Englisch.

Taschenbuch. Condición: 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.…