AIMC Topic: Carcinoma, Squamous Cell
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Deep learning prediction of esophageal squamous cell carcinoma invasion depth from arterial phase enhanced CT images: a binary classification approach.
BMC medical informatics and decision making
Jan 2, 2024
BACKGROUND: Precise prediction of esophageal squamous cell carcinoma (ESCC) invasion depth is crucial not only for optimizing treatment plans but also for reducing the need for invasive procedures, consequently lowering complications and costs. Despi...
Artificial intelligence for oral squamous cell carcinoma detection based on oral photographs: A comprehensive literature review.
Cancer medicine
Jan 2, 2024
INTRODUCTION: Oral squamous cell carcinoma (OSCC) presents a significant global health challenge. The integration of artificial intelligence (AI) and computer vision holds promise for the early detection of OSCC through the analysis of digitized oral...
Machine learning based on magnetic resonance imaging and clinical parameters helps predict mesenchymal-epithelial transition factor expression in oral tongue squamous cell carcinoma: a pilot study.
Oral surgery, oral medicine, oral pathology and oral radiology
Dec 27, 2023
OBJECTIVES: This study aimed to develop machine learning models to predict phosphorylated mesenchymal-epithelial transition factor (p-MET) expression in oral tongue squamous cell carcinoma (OTSCC) using magnetic resonance imaging (MRI)-derived textur...
A deep learning and radiomics fusion model based on contrast-enhanced computer tomography improves preoperative identification of cervical lymph node metastasis of oral squamous cell carcinoma.
Clinical oral investigations
Dec 27, 2023
OBJECTIVES: In this study, we constructed and validated models based on deep learning and radiomics to facilitate preoperative diagnosis of cervical lymph node metastasis (LNM) using contrast-enhanced computed tomography (CECT).
SkinViT: A transformer based method for Melanoma and Nonmelanoma classification.
PloS one
Dec 27, 2023
Over the past few decades, skin cancer has emerged as a major global health concern. The efficacy of skin cancer treatment greatly depends upon early diagnosis and effective treatment. The automated classification of Melanoma and Nonmelanoma is quite...
Diagnosis with confidence: deep learning for reliable classification of laryngeal dysplasia.
Histopathology
Oct 23, 2023
BACKGROUND: Diagnosis of head and neck (HN) squamous dysplasias and carcinomas is critical for patient care, cure, and follow-up. It can be challenging, especially for grading intraepithelial lesions. Despite recent simplification in the last WHO gra...
A deep learning algorithm to detect cutaneous squamous cell carcinoma on frozen sections in Mohs micrographic surgery: A retrospective assessment.
Experimental dermatology
Oct 21, 2023
Intraoperative margin analysis is crucial for the successful removal of cutaneous squamous cell carcinomas (cSCC). Artificial intelligence technologies (AI) have previously demonstrated potential for facilitating rapid and complete tumour removal usi...
Artificial intelligence-based diagnosis of the depth of laryngopharyngeal cancer.
Auris, nasus, larynx
Oct 12, 2023
OBJECTIVE: Transoral surgery (TOS) is a widely used treatment for laryngopharyngeal cancer. There are some difficult cases of setting the extent of resection in TOS, particularly in setting the vertical margins. However, positive vertical margins req...
Applying an artificial intelligence deep learning approach to routine dermatopathological diagnosis of basal cell carcinoma.
Journal der Deutschen Dermatologischen Gesellschaft = Journal of the German Society of Dermatology : JDDG
Oct 9, 2023
BACKGROUND: Institutes of dermatopathology are faced with considerable challenges including a continuously rising numbers of submitted specimens and a shortage of specialized health care practitioners. Basal cell carcinoma (BCC) is one of the most co...
Prognostic significance of cyclin D1 expression pattern in HPV-negative oral and oropharyngeal carcinoma: A deep-learning approach.
Journal of oral pathology & medicine : official publication of the International Association of Oral Pathologists and the American Academy of Oral Pathology
Sep 13, 2023
BACKGROUND: We aimed to establish image recognition and survival prediction models using a novel scoring system of cyclin D1 expression pattern in patients with human papillomavirus-negative oral or oropharyngeal squamous cell carcinoma.
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