AI-powered classification of oral pre-cancer: a histopathological image approach

A high fatality rate characterises the prognosis outlook for oral cancer due to delayed diagnosis and significantly hinders the ‎advancements in early detection techniques. Traditional histological investigation, a cornerstone of precancerous lesion diagnosis, faces ‎substantial challenges in terms of labour intensity in manually processing tissue samples, is time-consuming and the inferences are mostly ‎guided by microscopic investigation. Therefore, a system is proposed for oral dysplasia grading from histopathological tissues using machine ‎learning. Distinguished from other methodologies, this approach incorporates a comprehensive array of features, not limited to cell nuclei ‎properties but also morphometric analysis of epithelial stratification and enhancements in digital pathology. Moreover, early pre-cancer ‎grading enhances the survival chances of patients by identifying abnormalities that might be missed through conventional examination. The ‎study presented here has an overall accuracy of 94%, considering the limited training cases available under each feature. This approach would ‎benefit both doctors and patients by streamlining the diagnostic process and improving its outcomes. The fundamentals of oral cancer ‎surgical management, when it comes to risk factors, regional predispositions, treatment response, and outcome, oral cavity squamous cell ‎carcinoma (OSCC) is a heterogeneous illness. Surgery is the main treatment option for oral malignancies, even though non-surgical ‎treatment is used in other head and neck subsites. Adjuvant treatment, such as radiation or chemoradiation, is then administered based on ‎the risk factors of the final histopathology. Before beginning treatment, a multidisciplinary tumor board must discuss each patient ‎and develop a treatment strategy. This chapter aims to explain the fundamental surgical concepts used in the reconstruction of defects and the ‎management of various oral cavity subsites. The surgical management the technical process of brain arteriovenous malformation (bAVM) ‎excision, patient selection for surgery, and perioperative care that optimizes the likelihood of the best result are all included in surgical ‎treatment‎.

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Publication Details

Journal
International Journal of Basic and Applied Sciences
Published
2025-05-23
DOI
https://doi.org/10.14419/8c1tmt79
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

AI-powered classification of oral pre-cancer: a histopathological image approach

Marcella Bellani, R Priya, G. Devanand Venkatasubbu, Sharmila Sengupta et al.
International Journal of Basic and Applied Sciences
Radiomics and Machine Learning in Medical Imaging
article

AI-powered classification of oral pre-cancer: a histopathological image approach

Marcella Bellani, R Priya, G. Devanand Venkatasubbu, Sharmila Sengupta, Anuj Bagad, Aayush Talreja, Dr Harsha Karwa
article en

Abstract

A high fatality rate characterises the prognosis outlook for oral cancer due to delayed diagnosis and significantly hinders the ‎advancements in early detection techniques. Traditional histological investigation, a cornerstone of precancerous lesion diagnosis, faces ‎substantial challenges in terms of labour intensity in manually processing tissue samples, is time-consuming and the inferences are mostly ‎guided by microscopic investigation. Therefore, a system is proposed for oral dysplasia grading from histopathological tissues using machine ‎learning. Distinguished from other methodologies, this approach incorporates a comprehensive array of features, not limited to cell nuclei ‎properties but also morphometric analysis of epithelial stratification and enhancements in digital pathology. Moreover, early pre-cancer ‎grading enhances the survival chances of patients by identifying abnormalities that might be missed through conventional examination. The ‎study presented here has an overall accuracy of 94%, considering the limited training cases available under each feature. This approach would ‎benefit both doctors and patients by streamlining the diagnostic process and improving its outcomes. The fundamentals of oral cancer ‎surgical management, when it comes to risk factors, regional predispositions, treatment response, and outcome, oral cavity squamous cell ‎carcinoma (OSCC) is a heterogeneous illness. Surgery is the main treatment option for oral malignancies, even though non-surgical ‎treatment is used in other head and neck subsites. Adjuvant treatment, such as radiation or chemoradiation, is then administered based on ‎the risk factors of the final histopathology. Before beginning treatment, a multidisciplinary tumor board must discuss each patient ‎and develop a treatment strategy. This chapter aims to explain the fundamental surgical concepts used in the reconstruction of defects and the ‎management of various oral cavity subsites. The surgical management the technical process of brain arteriovenous malformation (bAVM) ‎excision, patient selection for surgery, and perioperative care that optimizes the likelihood of the best result are all included in surgical ‎treatment‎.

International Journal of Basic and Applied SciencesVol. 14(1)
Government Dental College and Hospital (IN), Vivekananda Institute of Medical Sciences (IN)
Openalex Percentile: Top 82%
Radiomics and Machine Learning in Medical Imaging
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