Research progress and application of artificial intelligence in thyroid associated ophthalmopathy
J Diao, X Chen, Y Shen, J Li, Y Chen, L He… - Frontiers in Cell and …, 2023 - frontiersin.org
Thyroid-associated ophthalmopathy (TAO) is a complicated orbitopathy related to
dysthyroid, which severely destroys the facial appearance and life quality without medical …
dysthyroid, which severely destroys the facial appearance and life quality without medical …
T2‐Weighted MR Imaging‐Derived Radiomics for Pretreatment Determination of Therapeutic Response to Glucocorticoid in Patients With Thyroid‐Associated …
H Hu, L Chen, JL Zhang, W Chen… - Journal of Magnetic …, 2022 - Wiley Online Library
Background MR imaging has been applied to determine therapeutic response to
glucocorticoid (GC) before treatment in thyroid‐associated ophthalmopathy (TAO), while the …
glucocorticoid (GC) before treatment in thyroid‐associated ophthalmopathy (TAO), while the …
The innovative model based on artificial intelligence algorithms to predict recurrence risk of patients with postoperative breast cancer
L Zeng, L Liu, D Chen, H Lu, Y Xue, H Bi… - Frontiers in …, 2023 - frontiersin.org
Purpose This study aimed to develop a machine learning model to retrospectively study and
predict the recurrence risk of breast cancer patients after surgery by extracting the …
predict the recurrence risk of breast cancer patients after surgery by extracting the …
Relevant characteristics analysis using natural language processing and machine learning based on phenotypes and T-cell subsets in systemic lupus erythematosus …
X Gu, Y Jin, T Fu, X Zhang, T Li, Y Yang, R Li… - Frontiers in …, 2021 - frontiersin.org
Anxiety is frequently observed in patients with systemic lupus erythematosus (SLE) and the
immune system could act as a trigger for anxiety. To recognize abnormal T-cell and B-cell …
immune system could act as a trigger for anxiety. To recognize abnormal T-cell and B-cell …
Deep learning for patient-specific quality assurance of volumetric modulated arc therapy: Prediction accuracy and cost-sensitive classification performance
Purpose To evaluate a deep learning model's performance in predicting and classifying
patient-specific quality assurance (PSQA) results for volumetric modulated arc therapy …
patient-specific quality assurance (PSQA) results for volumetric modulated arc therapy …
Analyzing the patient isocenter positional accuracy with portal imaging acquired at different gantry angles and its dosimetrical impact on the dose delivery for head …
B Pandu, D Khanna, M Palanisamy… - Precision Radiation …, 2024 - Wiley Online Library
Objective This study aimed to analyze the effect of different gantry angles on portal imaging
in terms of isocenter shifts and their dosimetric impact on dose delivery. Methods Thirty …
in terms of isocenter shifts and their dosimetric impact on dose delivery. Methods Thirty …
In vivo EPID-based daily treatment error identification for volumetric-modulated arc therapy in head and neck cancers with a hierarchical convolutional neural network …
Y Zeng, H Li, Y Chang, Y Han, H Liu, B Pang… - … Engineering Sciences in …, 2024 - Springer
We proposed a deep learning approach to classify various error types in daily VMAT
treatment of head and neck cancer patients based on EPID dosimetry, which could provide …
treatment of head and neck cancer patients based on EPID dosimetry, which could provide …
[HTML][HTML] Machine learning-based ensemble prediction model for the gamma passing rate of VMAT-SBRT plan
W Sun, Z Mo, Y Li, J Xiao, L Jia, S Huang, C Liao, J Du… - Physica Medica, 2024 - Elsevier
Purpose The purpose of this study was to accurately predict or classify the beam GPR with
an ensemble model by using machine learning for SBRT (VMAT) plans. Methods A total of …
an ensemble model by using machine learning for SBRT (VMAT) plans. Methods A total of …