AIMC Topic: Mouth Neoplasms

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Deep learning-based artificial intelligence models predict survival in patients with oral cavity squamous cell carcinoma.

Scientific reports
Traditional survival predictions for oral squamous cell carcinoma (OSCC) rely on TNM staging, which lacks individualized prognostic value. Clinical factors such as performance status, age, sex, and lifestyle affect outcomes but are underrepresented i...

Detect pre-cancerous tongue lesions for early oral cancer diagnosis using deep learning algorithm.

Scientific reports
Precancerous tongue lesion is a prevalent, complex, and highly perilous kind of cancer. The tumour might be in the salivary glands, tonsils, neck, cheek, and mouth. Oral Cancer (OC) is commonly identified in advanced stages due to the limited accurac...

Dual smart monitoring and predictive non-destructive evaluation: A review of advanced hydrogel and stem cell-based strategies for oral cancer theragnostic applications.

International journal of pharmaceutics
Oral cancer remains one of the most aggressive malignancies worldwide, with high recurrence and limited treatment outcomes due to late diagnosis and ineffective targeting of tumor microenvironments. Stem cell-based hydrogel therapies have emerged as ...

Micrometastasis and Isolated Tumor Cells in Oral Squamous Cell Carcinoma: Refining Nodal Staging with Emerging Technologies.

Head and neck pathology
PURPOSE: Cervical lymph node metastasis significantly influence prognosis in oral squamous cell carcinoma (OSCC), guiding staging, treatment decisions, and overall survival. Sentinel lymph node biopsy (SLNB) offers a minimally invasive approach for e...

Differentiation of benign and malignant oral lesions through surface texture analysis and SVM modeling.

Clinical oral investigations
OBJECTIVES: To evaluate the diagnostic potential of surface texture features extracted from clinical images in objectively differentiating benign from malignant oral lesions, and to validate classification performance of a Support Vector Machine (SVM...

Lipid metabolites as biomarkers and therapeutic targets in oral squamous cell carcinoma.

BMC oral health
This study explores the association of lipid metabolism disruption and Oral Squamous Cell Carcinoma (OSCC). We aim to identify specific lipid biomarkers and therapeutic targets for OSCC. We included 78 OSCC patients and 80 healthy controls, and appli...

Performance of deep learning models for the classification and object detection of different oral white lesions using photographic images.

Scientific reports
Computer vision adjunctive technology for oral lesion diagnoses has been developed to detect and identify Oral Potentially Malignant Disorders (OPMDs) and non-OPMDs. The early detection of OPMDs can reduce the risk of oral cancer development, improvi...

Oral cancer detection via Vanilla CNN optimized by improved artificial protozoa optimizer.

Scientific reports
In this study, we propose a new method for oral cancer detection using a modified Vanilla Convolutional Neural Network (CNN) architecture with incorporated batch normalization, dropout regularization, and a customized design structure for the convolu...

Unraveling prognostic biomarkers in oral squamous cell carcinoma: An approach based on explainable artificial intelligence.

Cancer genetics
Oral cancer is among the top malignancies and the leading cause of death worldwide. Poor outcomes are attributed to local recurrence and distant metastasis of disease. There is an urgent need to identify the potential biomarkers that may help in prog...

AgNWs-COF SERS biosensor for oral cancer diagnosis based on exhaled breath and saliva.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Over recent years, surface-enhanced Raman spectroscopy (SERS) has shown its unparalleled sensitivity and molecular specificity in biomedical applications. However, noninvasive and sensitive detection of biomarkers with conventional SERS for oral canc...