The feasibility study on the generalization of deep learning dose prediction model for volumetric modulated arc therapy of cervical cancer
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Applied Clinical Medical Physics"
DOI: 10.1002/acm2.13583
Abstract: Abstract Purpose To develop a 3D‐Unet dose prediction model to predict the three‐dimensional dose distribution of volumetric modulated arc therapy (VMAT) for cervical cancer and test the dose prediction performance of the model in endometrial… read more here.
Keywords: cervical cancer; endometrial cancer; dose prediction; model ... See more keywords
TrDosePred: A deep learning dose prediction algorithm based on transformers for head and neck cancer radiotherapy.
Sign Up to like & getrecommendations! Published in 2023 at "Journal of applied clinical medical physics"
DOI: 10.1002/acm2.13942
Abstract: BACKGROUND Intensity-Modulated Radiation Therapy (IMRT) has been the standard of care for many types of tumors. However, treatment planning for IMRT is a time-consuming and labor-intensive process. PURPOSE To alleviate this tedious planning process, a… read more here.
Keywords: prediction algorithm; head neck; based transformers; prediction ... See more keywords
A portal dosimetry dose prediction method based on collapsed cone algorithm using the clinical beam model
Sign Up to like & getrecommendations! Published in 2017 at "Medical Physics"
DOI: 10.1002/mp.12018
Abstract: Purpose: Amorphous silicon electronical portal imaging devices (EPIDs) are widely used for dosimetric measurements in Radiation Therapy. The purpose of this work was to determine if a portal dose prediction method can be utilized for… read more here.
Keywords: prediction method; dose prediction; method; model ... See more keywords
Feasibility study of fast intensity-modulated proton therapy dose prediction method using deep neural networks for prostate cancer.
Sign Up to like & getrecommendations! Published in 2022 at "Medical physics"
DOI: 10.1002/mp.15702
Abstract: PURPOSE Compared to the pencil-beam algorithm, the Monte-Carlo (MC) algorithm is more accurate for dose calculation but time-consuming in proton therapy. To solve this problem, this study uses deep learning to provide fast 3D dose… read more here.
Keywords: prostate cancer; dose; prediction; proton therapy ... See more keywords
Small beams, fast predictions A comparison of machine learning dose prediction models for proton minibeam therapy.
Sign Up to like & getrecommendations! Published in 2022 at "Medical physics"
DOI: 10.1002/mp.16066
Abstract: BACKGROUND Dose calculations for novel radiotherapy cancer treatments such as proton minibeam radiation therapy is often done using full Monte Carlo (MC) simulations. As MC simulations can be very time consuming for this kind of… read more here.
Keywords: prediction; proton minibeam; dose prediction; minibeam therapy ... See more keywords
Sub-second photon dose prediction via transformer neural networks.
Sign Up to like & getrecommendations! Published in 2022 at "Medical physics"
DOI: 10.1002/mp.16231
Abstract: BACKGROUND Fast dose calculation is critical for online and real time adaptive therapy workflows. While modern physics-based dose algorithms must compromise accuracy to achieve low computation times, deep learning models can potentially perform dose prediction… read more here.
Keywords: dose; dose prediction; photon dose; photon ... See more keywords
Incorporating historical sub-optimal deep neural networks for dose prediction in radiotherapy
Sign Up to like & getrecommendations! Published in 2021 at "Medical image analysis"
DOI: 10.1016/j.media.2020.101886
Abstract: As the main treatment for cancer patients, radiotherapy has achieved enormous advancement over recent decades. However, these achievements have come at the cost of increased treatment plan complexity, necessitating high levels of expertise experience and… read more here.
Keywords: neural networks; sub optimal; dose prediction; prediction ... See more keywords
Incorporating dosimetric features into the prediction of 3D VMAT dose distributions using deep convolutional neural network.
Sign Up to like & getrecommendations! Published in 2019 at "Physics in medicine and biology"
DOI: 10.1088/1361-6560/ab2146
Abstract: An accurate prediction of achievable dose distribution on a patient specific basis would greatly improve IMRT/VMAT planning in both efficiency and quality. Recently machine learning techniques have been proposed for IMRT dose prediction based on… read more here.
Keywords: deep convolutional; convolutional neural; dose prediction; neural network ... See more keywords
Performance Evaluation of Warfarin Dose Prediction Algorithms and Effects of Clinical Factors on Warfarin Dose in Chinese Patients.
Sign Up to like & getrecommendations! Published in 2021 at "Therapeutic drug monitoring"
DOI: 10.1097/ftd.0000000000000880
Abstract: BACKGROUND The clinical utility of warfarin dose prediction algorithms remains controversial, our purpose is to evaluate the performance of warfarin dose prediction algorithms and the effects of clinical factors on warfarin dose in Chinese patients.… read more here.
Keywords: dose prediction; warfarin dose; prediction algorithms; warfarin ... See more keywords
A Post-Hoc Interpretable Ensemble Model to Feature Effect Analysis in Warfarin Dose Prediction for Chinese Patients
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DOI: 10.1109/jbhi.2021.3092170
Abstract: To interprete the importance of clinical features and genotypes for warfarin daily dose prediction, we developed a post-hoc interpretable framework based on an ensemble predictive model. This framework includes permutation importance for global interpretation and… read more here.
Keywords: predictive model; model; hoc interpretable; dose prediction ... See more keywords
Accuracy Improvement Method Based on Characteristic Database Classification for IMRT Dose Prediction in Cervical Cancer: Scientifically Training Data Selection
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Oncology"
DOI: 10.3389/fonc.2022.808580
Abstract: Purpose Consistent training and testing datasets can lead to good performance for deep learning (DL) models. However, a large high-quality training dataset for unusual clinical scenarios is usually not easy to collect. The work aims… read more here.
Keywords: beam; prediction; dose prediction; model ... See more keywords