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Showing 1429-1449 of 6,118 articles

Machine learning for prediction of chemoradiation therapy response in rectal cancer using pre-treatment and mid-radiation multi-parametric MRI.

PURPOSE: To predict the neoadjuvant chemoradiation therapy (CRT) response in patients with locally a...

May 2019 31059768

Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithm.

Recent analysis identified distinct genomic subtypes of lower-grade glioma tumors which are associat...

May 2019 31078126

A deep learning radiomics model for preoperative grading in meningioma.

OBJECTIVES: To noninvasively differentiate meningioma grades by deep learning radiomics (DLR) model ...

May 2019 31153553

A Novel Method for Classifying Liver and Brain Tumors Using Convolutional Neural Networks, Discrete Wavelet Transform and Long Short-Term Memory Networks.

Rapid classification of tumors that are detected in the medical images is of great importance in the...

Apr 2019 31035406

Multimodal brain tumor image segmentation using WRN-PPNet.

Tumor segmentation is of great importance for diagnosis and prognosis of brain cancer in medical fie...

Apr 2019 31154088

Attention-aware fully convolutional neural network with convolutional long short-term memory network for ultrasound-based motion tracking.

PURPOSE: One of the promising options for motion management in radiation therapy (RT) is the use of ...

Apr 2019 30912590

A quantitative SVM approach potentially improves the accuracy of magnetic resonance spectroscopy in the preoperative evaluation of the grades of diffuse gliomas.

OBJECTIVES: To investigate the association between proton magnetic resonance spectroscopy (H-MRS) me...

Apr 2019 31035232

Machine-learning based radiogenomics analysis of MRI features and metagenes in glioblastoma multiforme patients with different survival time.

BACKGROUND: This study aimed to examine multi-dimensional MRI features' predictability on survival o...

Apr 2019 31001929

Machine Learning to Build and Validate a Model for Radiation Pneumonitis Prediction in Patients with Non-Small Cell Lung Cancer.

PURPOSE: Radiation pneumonitis is an important adverse event in patients with non-small cell lung ca...

Apr 2019 30992302

MRI-only brain radiotherapy: Assessing the dosimetric accuracy of synthetic CT images generated using a deep learning approach.

PURPOSE: This study assessed the dosimetric accuracy of synthetic CT images generated from magnetic ...

Apr 2019 31015130

Combining handcrafted features with latent variables in machine learning for prediction of radiation-induced lung damage.

PURPOSE: There has been burgeoning interest in applying machine learning methods for predicting radi...

Apr 2019 30891794

Automated quantitative tumour response assessment of MRI in neuro-oncology with artificial neural networks: a multicentre, retrospective study.

BACKGROUND: The Response Assessment in Neuro-Oncology (RANO) criteria and requirements for a uniform...

Apr 2019 30952559

Dosimetric study on learning-based cone-beam CT correction in adaptive radiation therapy.

INTRODUCTION: Cone-beam CT (CBCT) image quality is important for its quantitative analysis in adapti...

Apr 2019 30948341

Deep Learning for Automated Contouring of Primary Tumor Volumes by MRI for Nasopharyngeal Carcinoma.

Background Nasopharyngeal carcinoma (NPC) may be cured with radiation therapy. Tumor proximity to cr...

Mar 2019 30912722

Application of a machine learning method to whole brain white matter injury after radiotherapy for nasopharyngeal carcinoma.

BACKGROUND: The purpose/aim of this study was to 1) use magnetic resonance diffusion tensor imaging ...

Mar 2019 30909974

Oncology/Hematology

Browse Categories

Machine learning for prediction of chemoradiation therapy response in rectal cancer using pre-treatment and mid-radiation multi-parametric MRI.

Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithm.

A deep learning radiomics model for preoperative grading in meningioma.

A Novel Method for Classifying Liver and Brain Tumors Using Convolutional Neural Networks, Discrete Wavelet Transform and Long Short-Term Memory Networks.

Multimodal brain tumor image segmentation using WRN-PPNet.

Attention-aware fully convolutional neural network with convolutional long short-term memory network for ultrasound-based motion tracking.

A quantitative SVM approach potentially improves the accuracy of magnetic resonance spectroscopy in the preoperative evaluation of the grades of diffuse gliomas.

Machine-learning based radiogenomics analysis of MRI features and metagenes in glioblastoma multiforme patients with different survival time.

Machine Learning to Build and Validate a Model for Radiation Pneumonitis Prediction in Patients with Non-Small Cell Lung Cancer.

MRI-only brain radiotherapy: Assessing the dosimetric accuracy of synthetic CT images generated using a deep learning approach.

Combining handcrafted features with latent variables in machine learning for prediction of radiation-induced lung damage.

Automated quantitative tumour response assessment of MRI in neuro-oncology with artificial neural networks: a multicentre, retrospective study.

Dosimetric study on learning-based cone-beam CT correction in adaptive radiation therapy.

Deep Learning for Automated Contouring of Primary Tumor Volumes by MRI for Nasopharyngeal Carcinoma.

Application of a machine learning method to whole brain white matter injury after radiotherapy for nasopharyngeal carcinoma.

A modality-adaptive method for segmenting brain tumors and organs-at-risk in radiation therapy planning.

Glioma Tumor Grade Identification Using Artificial Intelligent Techniques.

Group Lasso Regularized Deep Learning for Cancer Prognosis from Multi-Omics and Clinical Features.

Differentiation of glioblastoma from solitary brain metastases using radiomic machine-learning classifiers.

Neural Networks for Deep Radiotherapy Dose Analysis and Prediction of Liver SBRT Outcomes.

Accurate Patient-Specific Machine Learning Models of Glioblastoma Invasion Using Transfer Learning.

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