AIMC Topic: Tongue Neoplasms
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A tailored deep learning approach for early detection of oral cancer using a 19-layer CNN on clinical lip and tongue images.
Scientific reports
Jul 4, 2025
Early and accurate detection of oral cancer plays a pivotal role in improving patient outcomes. This research introduces a custom-designed, 19-layer convolutional neural network (CNN) for the automated diagnosis of oral cancer using clinical images o...
Assessment of established prognostic factors and artificial intelligence-based evaluation of tumor-infiltrating lymphocytes in oral tongue squamous cell carcinoma.
Oral oncology
Jul 3, 2025
BACKGROUND: Traditional risk assessment for tongue cancer relies on clinicopathological parameters. Although tumor-infiltrating lymphocytes (TILs) are promising prognostic markers, their evaluation lacks standardization. This study aimed to validate ...
An assessment of the influence of trade-off optimization in commercial knowledge based planning library creation for tongue cancer patients.
Medical dosimetry : official journal of the American Association of Medical Dosimetrists
Dec 6, 2024
This article aims to compare the dosimetric performance between knowledge-based plan (KBP) libraries with and without trade-off (TO) exploration using multicriterial optimization (MCO) for tongue cancer patients. The trade-off optimized library (KBP_...
Letter to the editor: Magnetic resonance imaging-based radiomics and deep learning models for predicting lymph node metastasis of squamous cell carcinoma of the tongue.
Oral surgery, oral medicine, oral pathology and oral radiology
May 3, 2024
Magnetic resonance imaging-based radiomics and deep learning models for predicting lymph node metastasis of squamous cell carcinoma of the tongue.
Oral surgery, oral medicine, oral pathology and oral radiology
Feb 3, 2024
OBJECTIVE: This study aimed to establish a combined method of radiomics and deep learning (DL) in magnetic resonance imaging (MRI) to predict lymph node metastasis (LNM) preoperatively in patients with squamous cell carcinoma of the tongue.
Implementing a deep learning model for automatic tongue tumour segmentation in ex-vivo 3-dimensional ultrasound volumes.
The British journal of oral & maxillofacial surgery
Jan 3, 2024
Three-dimensional (3D) ultrasound can assess the margins of resected tongue carcinoma during surgery. Manual segmentation (MS) is time-consuming, labour-intensive, and subject to operator variability. This study aims to investigate use of a 3D deep l...
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...
Predictive modeling of dose-volume parameters of carcinoma tongue cases using machine learning models.
Medical dosimetry : official journal of the American Association of Medical Dosimetrists
Oct 31, 2023
The aim of this study is to create a single institution-based machine learning model for a dose prediction generation tool for post-operative carcinoma of the tongue cases prospectively. Intensity-modulated radiotherapy (IMRT) plans for 20 patients w...
Advanced-stage tongue squamous cell carcinoma: a machine learning model for risk stratification and treatment planning.
Acta oto-laryngologica
Feb 15, 2023
BACKGROUND: A significant number of tongue squamous cell carcinoma (TSCC) patients are diagnosed at late stage.
Transoral robotic cordectomy for glottic carcinoma: a rapid review.
European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
Jun 22, 2022
OBJECTIVE: The objective of this study was to investigate feasibility, surgical, oncological, and functional outcomes of transoral robotic cordectomy (TORS-Co) and whether TORS-Co reported comparable outcomes of transoral laser microsurgery (TLM).
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