AIMC Topic: Mouth Neoplasms

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Oral mucosal lesions triage via YOLOv7 models.

Journal of the Formosan Medical Association = Taiwan yi zhi
BACKGROUND/PURPOSE: The global incidence of lip and oral cavity cancer continues to rise, necessitating improved early detection methods. This study leverages the capabilities of computer vision and deep learning to enhance the early detection and cl...

Detection of oral cancer and oral potentially malignant disorders using artificial intelligence-based image analysis.

Head & neck
BACKGROUND: We aimed to construct an artificial intelligence-based model for detecting oral cancer and dysplastic leukoplakia using oral cavity images captured with a single-lens reflex camera.

Feasibility study of ResNet-50 in the distinction of intraoral neural tumors using histopathological images.

Journal of oral pathology & medicine : official publication of the International Association of Oral Pathologists and the American Academy of Oral Pathology
BACKGROUND: Neural tumors are difficult to distinguish based solely on cellularity and often require immunohistochemical staining to aid in identifying the cell lineage. This article investigates the potential of a Convolutional Neural Network for th...

Utilizing deep learning for automated detection of oral lesions: A multicenter study.

Oral oncology
OBJECTIVES: We aim to develop a YOLOX-based convolutional neural network model for the precise detection of multiple oral lesions, including OLP, OLK, and OSCC, in patient photos.

Enhancing oral squamous cell carcinoma detection: a novel approach using improved EfficientNet architecture.

BMC oral health
PROBLEM: Oral squamous cell carcinoma (OSCC) is the eighth most prevalent cancer globally, leading to the loss of structural integrity within the oral cavity layers and membranes. Despite its high prevalence, early diagnosis is crucial for effective ...

The innovation of AI-based software in oral diseases: clinical-histopathological correlation diagnostic accuracy primary study.

BMC oral health
BACKGROUND: Machine learning (ML) through artificial intelligence (AI) could provide clinicians and oral pathologists to advance diagnostic problems in the field of potentially malignant lesions, oral cancer, periodontal diseases, salivary gland dise...

An Update on the Use of Artificial Intelligence in Digital Pathology for Oral Epithelial Dysplasia Research.

Head and neck pathology
INTRODUCTION: Oral epithelial dysplasia (OED) is a precancerous histopathological finding which is considered the most important prognostic indicator for determining the risk of malignant transformation into oral squamous cell carcinoma (OSCC). The g...