Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing Jun 2026, 2026
ISBN 10: 6630091620 ISBN 13: 9786630091625
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 66,90
Quantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 128 pp. Englisch.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2026
ISBN 10: 6630091620 ISBN 13: 9786630091625
Da: preigu, Osnabrück, Germania
EUR 56,45
Quantità: 5 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: 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.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing Jun 2026, 2026
ISBN 10: 6630091620 ISBN 13: 9786630091625
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 66,90
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware 128 pp. Englisch.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2026
ISBN 10: 6630091620 ISBN 13: 9786630091625
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 67,70
Quantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: 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.