AIMC Topic: Nasopharyngeal Carcinoma
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Comparative evaluation of machine learning models in predicting overall survival for nasopharyngeal carcinoma using F-FDG PET-CT parameters.
Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
Sep 20, 2024
PURPOSE: The objective of this study is to assess the prognostic efficacy of F-fluorodeoxyglucose (F-FDG) positron emission tomography/computed tomography (PET-CT) parameters in nasopharyngeal carcinoma (NPC) and identify the best machine learning (M...
Deep learning method for predicting weekly anatomical changes in patients with nasopharyngeal carcinoma during radiotherapy.
Medical physics
Sep 3, 2024
BACKGROUND: Patients may undergo anatomical changes during radiotherapy, leading to an underdosing of the target or overdosing of the organs at risk (OARs).
Improving the performance of deep learning models in predicting and classifying gamma passing rates with discriminative features and a class balancing technique: a retrospective cohort study.
Radiation oncology (London, England)
Jul 31, 2024
BACKGROUND: The purpose of this study was to improve the deep learning (DL) model performance in predicting and classifying IMRT gamma passing rate (GPR) by using input features related to machine parameters and a class balancing technique.
Machine learning-derived prognostic signature for progression-free survival in non-metastatic nasopharyngeal carcinoma.
Head & neck
Jul 30, 2024
BACKGROUND: Early detection of high-risk nasopharyngeal carcinoma (NPC) recurrence is essential. We created a machine learning-derived prognostic signature (MLDPS) by combining three machine learning (ML) models to predict progression-free survival (...
A pretreatment multiparametric MRI-based radiomics-clinical machine learning model for predicting radiation-induced temporal lobe injury in patients with nasopharyngeal carcinoma.
Head & neck
Jun 18, 2024
BACKGROUND: To establish and validate a machine learning model using pretreatment multiparametric magnetic resonance imaging-based radiomics data with clinical data to predict radiation-induced temporal lobe injury (RTLI) in patients with nasopharyng...
A deep learning-based method for the prediction of temporal lobe injury in patients with nasopharyngeal carcinoma.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Apr 22, 2024
PURPOSE: To establish a deep learning-based model to predict radiotherapy-induced temporal lobe injury (TLI).
Radiomics and Deep Learning in Nasopharyngeal Carcinoma: A Review.
IEEE reviews in biomedical engineering
Jan 12, 2024
Nasopharyngeal carcinoma is a common head and neck malignancy with distinct clinical management compared to other types of cancer. Precision risk stratification and tailored therapeutic interventions are crucial to improving the survival outcomes. Ar...
Prognosis Forecast of Re-Irradiation for Recurrent Nasopharyngeal Carcinoma Based on Deep Learning Multi-Modal Information Fusion.
IEEE journal of biomedical and health informatics
Dec 5, 2023
Radiation therapy is the primary treatment for recurrent nasopharyngeal carcinoma. However, it may induce necrosis of the nasopharynx, leading to severe complications such as bleeding and headache. Therefore, forecasting necrosis of the nasopharynx a...
Deep learning-based recurrence detector on magnetic resonance scans in nasopharyngeal carcinoma: A multicenter study.
European journal of radiology
Sep 14, 2023
OBJECTIVES: Accuracy in the detection of recurrent nasopharyngeal carcinoma (NPC) on follow-up magnetic resonance (MR) scans needs to be improved.
Multi-task deep learning-based radiomic nomogram for prognostic prediction in locoregionally advanced nasopharyngeal carcinoma.
European journal of nuclear medicine and molecular imaging
Aug 19, 2023
PURPOSE: Prognostic prediction is crucial to guide individual treatment for locoregionally advanced nasopharyngeal carcinoma (LA-NPC) patients. Recently, multi-task deep learning was explored for joint prognostic prediction and tumor segmentation in ...
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