Lung Cancer

A feasibility study for predicting optimal radiation therapy dose distributions of prostate cancer patients from patient anatomy using deep learning.

With the advancement of treatment modalities in radiation therapy for cancer patients, outcomes have...

Machine Learning to Predict Delays in Adjuvant Radiation following Surgery for Head and Neck Cancer.

OBJECTIVE: To apply a novel methodology with machine learning (ML) to a large national cancer regist...

Predicting radiation pneumonitis in locally advanced stage II-III non-small cell lung cancer using machine learning.

BACKGROUND AND PURPOSE: Radiation pneumonitis (RP) is a radiotherapy dose-limiting toxicity for loca...

Balance Impairment in Radiation Induced Leukoencephalopathy Patients Is Coupled With Altered Visual Attention in Natural Tasks.

Recent studies have shown that alterations in executive function and attention lead to balance cont...

Intervening Nidal Brain Parenchyma and Risk of Radiation-Induced Changes After Radiosurgery for Brain Arteriovenous Malformation: A Study Using an Unsupervised Machine Learning Algorithm.

OBJECTIVE: To assess the sensitivity and specificity of arteriovenous malformation (AVM) nidal compo...

Early esophageal adenocarcinoma detection using deep learning methods.

PURPOSE: This study aims to adapt and evaluate the performance of different state-of-the-art deep le...

Liver Extraction Using Residual Convolution Neural Networks From Low-Dose CT Images.

An efficient and precise liver extraction from computed tomography (CT) images is a crucial step for...

Sleep Duration and Diabetic Kidney Disease.

Abnormally short or long durations of sleep have been proposed as a risk factors for diabetes and i...

Optimization based trajectory planning for real-time 6DoF robotic patient motion compensation systems.

PURPOSE: Robotic stabilization of a therapeutic radiation beam with respect to a dynamically moving ...

Simultaneous cosegmentation of tumors in PET-CT images using deep fully convolutional networks.

PURPOSE: To investigate the use and efficiency of 3-D deep learning, fully convolutional networks (D...

Machine learning-based radiomic models to predict intensity-modulated radiation therapy response, Gleason score and stage in prostate cancer.

OBJECTIVE: To develop different radiomic models based on the magnetic resonance imaging (MRI) radiom...

Design and synthesis of new phthalazine-based derivatives as potential EGFR inhibitors for the treatment of hepatocellular carcinoma.

Searching for new leads in the battle of cancer will never ends, we herein disclose the design and s...

Intensity-modulated radiation therapy of anal squamous cell carcinoma: Relationship between delineation quality and regional recurrence.

BACKGROUND AND PURPOSE: Intensity-modulated radiation therapy (IMRT) is currently indicated to treat...

Predictors of Nodal and Metastatic Failure in Early Stage Non-small-cell Lung Cancer After Stereotactic Body Radiation Therapy.

INTRODUCTION/BACKGROUND: Many patients with early stage non-small-cell lung cancer (ES-NSCLC) underg...

Automated data extraction and ensemble methods for predictive modeling of breast cancer outcomes after radiation therapy.

PURPOSE: The purpose of this study was to compare the effectiveness of ensemble methods (e.g., rando...

Cycle-consistent adversarial denoising network for multiphase coronary CT angiography.

PURPOSE: In multiphase coronary CT angiography (CTA), a series of CT images are taken at different l...

MILD-Net: Minimal information loss dilated network for gland instance segmentation in colon histology images.

The analysis of glandular morphology within colon histopathology images is an important step in dete...

Ultra-Low-Dose Neck CT With Low-Dose Contrast Material for Preoperative Staging of Thyroid Cancer: Image Quality and Diagnostic Performance.

OBJECTIVE: Although CT has been used as a complementary diagnostic method for the preoperative diagn...

Protective effect of polysaccharide from Sophora japonica L. flower buds against UVB radiation in a human keratinocyte cell line (HaCaT cells).

Natured botanical extract has attracted considerable attention recently in the field of skin anti-ul...

Computer-aided diagnosis using deep learning in the evaluation of early oesophageal adenocarcinoma.

Robot-assisted intravertebral augmentation corrects local kyphosis more effectively than a conventional fluoroscopy-guided technique.

OBJECTIVEIntravertebral augmentation (IVA) is a reliable minimally invasive technique for treating M...