AIMC Topic: Mouth Neoplasms

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Deep learning assisted contrast-enhanced CT-based diagnosis of cervical lymph node metastasis of oral cancer: a retrospective study of 1466 cases.

European radiology
OBJECTIVES: Lymph node (LN) metastasis is a common cause of recurrence in oral cancer; however, the accuracy of distinguishing positive and negative LNs is not ideal. Here, we aimed to develop a deep learning model that can identify, locate, and dist...

Comparing Free-Flap Reconstruction After Robot-Assisted Neck Dissection via a Retroauricular Approach and a Traditional Transcervical Approach: Single-Surgeon Experiences of 90 Consecutive Cases.

Annals of surgical oncology
BACKGROUND: Predominant traditional approaches for most patients who have advanced-stage oral cancer with transcervical incision lines left irreversible scars. To address this, surgeons have continuously refined minimally invasive surgery (MIS) techn...

Artificial intelligence for oral cancer diagnosis: What are the possibilities?

Oral oncology
Oral cancer could be prevented. The primary strategy is based on prevention. Most patients with oral cancer present to the hospital network with advanced staging and a low chance of cure. This condition may be related to physicians' difficulty of mak...

Identifying Drug Targets of Oral Squamous Cell Carcinoma through a Systems Biology Method and Genome-Wide Microarray Data for Drug Discovery by Deep Learning and Drug Design Specifications.

International journal of molecular sciences
In this study, we provide a systems biology method to investigate the carcinogenic mechanism of oral squamous cell carcinoma (OSCC) in order to identify some important biomarkers as drug targets. Further, a systematic drug discovery method with a dee...

Field validation of deep learning based Point-of-Care device for early detection of oral malignant and potentially malignant disorders.

Scientific reports
Early detection of oral cancer in low-resource settings necessitates a Point-of-Care screening tool that empowers Frontline-Health-Workers (FHW). This study was conducted to validate the accuracy of Convolutional-Neural-Network (CNN) enabled m(mobile...

Intelligent Deep Learning Enabled Oral Squamous Cell Carcinoma Detection and Classification Using Biomedical Images.

Computational intelligence and neuroscience
Oral cancer is one of the lethal diseases among the available malignant tumors globally, and it has become a challenging health issue in developing and low-to-middle income countries. The prognosis of oral cancer remains poor because over 50% of pati...

A machine learning model for separating epithelial and stromal regions in oral cavity squamous cell carcinomas using H&E-stained histology images: A multi-center, retrospective study.

Oral oncology
OBJECTIVE: Tissue slides from Oral cavity squamous cell carcinoma (OC-SCC), particularly the epithelial regions, hold morphologic features that are both diagnostic and prognostic. Yet, previously developed approaches for automated epithelium segmenta...

The Effectiveness of Artificial Intelligence in Detection of Oral Cancer.

International dental journal
AIM: The early detection of oral cancer (OC) at the earliest stage significantly increases survival rates. Recently, there has been an increasing interest in the use of artificial intelligence (AI) technologies in diagnostic medicine. This study aime...