Computational Pathology in Oral Potentially Malignant Disorders (Paperback)
Language: English
Published by LAP Lambert Academic Publishing, 2026
- Softcover
- New

Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
AbeBooks seller since October 12, 2005
Condition: New
US$ 87.99
Quantity: 1 available
Add to basketItem description from seller
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
- Title
- Computational Pathology in Oral Potentially Malignant Disorders (Paperback)
- Author
- Smitha Kuttappan
- Publisher
- LAP Lambert Academic Publishing
- Publication year
- 2026
- Condition
- new
- Binding
- Paperback
- Language
- English
- ISBN 10
- 6630091620
- ISBN 13
- 9786630091625
"Synopsis" may belong to another edition of this title.
Grand Eagle Retail
Bensenville, IL, U.S.A.
AbeBooks seller since October 12, 2005
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APOLLO ONLINE CORP.
605 Geddes Street
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