Lung Cancer

A Machine-Learning Approach Using PET-Based Radiomics to Predict the Histological Subtypes of Lung Cancer.

PURPOSE: We sought to distinguish lung adenocarcinoma (ADC) from squamous cell carcinoma using a mac...

A convolutional neural network approach for IMRT dose distribution prediction in prostate cancer patients.

The purpose of the study was to compare a 3D convolutional neural network (CNN) with the conventiona...

Full-Dose PET Image Estimation from Low-Dose PET Image Using Deep Learning: a Pilot Study.

Positron emission tomography (PET) imaging is an effective tool used in determining disease stage an...

Machine-Learning and Stochastic Tumor Growth Models for Predicting Outcomes in Patients With Advanced Non-Small-Cell Lung Cancer.

PURPOSE: The prediction of clinical outcomes for patients with cancer is central to precision medici...

The Role of Generative Adversarial Networks in Radiation Reduction and Artifact Correction in Medical Imaging.

Adversarial networks were developed to complete powerful image-processing tasks on the basis of exam...

Using Artificial Intelligence to Improve the Quality and Safety of Radiation Therapy.

Within artificial intelligence, machine learning (ML) efforts in radiation oncology have augmented t...

Lens Identification to Prevent Radiation-Induced Cataracts Using Convolutional Neural Networks.

Exposure of the lenses to direct ionizing radiation during computed tomography (CT) examinations pre...

Deep Learning Based Dosimetry Evaluation at Organs-at-Risk in Esophageal Radiation Treatment Planning.

Rapid esophageal radiation treatment planning is often obstructed by manually adjusting optimization...

Application of deep learning (3-dimensional convolutional neural network) for the prediction of pathological invasiveness in lung adenocarcinoma: A preliminary study.

To compare results for radiological prediction of pathological invasiveness in lung adenocarcinoma b...

Restoration of Full Data from Sparse Data in Low-Dose Chest Digital Tomosynthesis Using Deep Convolutional Neural Networks.

Chest digital tomosynthesis (CDT) provides more limited image information required for diagnosis whe...

Effect of normalization methods on the performance of supervised learning algorithms applied to HTSeq-FPKM-UQ data sets: 7SK RNA expression as a predictor of survival in patients with colon adenocarcinoma.

MOTIVATION: One of the main challenges in machine learning (ML) is choosing an appropriate normaliza...

Exploring the survival prognosis of lung adenocarcinoma based on the cancer genome atlas database using artificial neural network.

The aim of this study was to investigate the clinical factors affecting the survival prognosis of lu...

Validity of Natural Language Processing for Ascertainment of and Test Results in SEER Cases of Stage IV Non-Small-Cell Lung Cancer.

PURPOSE: SEER registries do not report results of epidermal growth factor receptor () and anaplastic...

Use of Crowd Innovation to Develop an Artificial Intelligence-Based Solution for Radiation Therapy Targeting.

IMPORTANCE: Radiation therapy (RT) is a critical cancer treatment, but the existing radiation oncolo...

STATISTICAL APPROACH FOR HUMAN ELECTROMAGNETIC EXPOSURE ASSESSMENT IN FUTURE WIRELESS ATTO-CELL NETWORKS.

In this article, we study human electromagnetic exposure to the radiation of an ultra dense network ...

MR-based treatment planning in radiation therapy using a deep learning approach.

PURPOSE: To develop and evaluate the feasibility of deep learning approaches for MR-based treatment ...

Radiomics - Using Artificial Intelligence in the Quest towards Personalised Radiation Treatment.

Screening key lncRNAs for human lung adenocarcinoma based on machine learning and weighted gene co-expression network analysis.

BACKGROUND: Lung adenocarcinoma (LUAD) accounts for a significant proportion of lung cancer and ther...

Iterative image reconstruction for sparse-view CT via total variation regularization and dictionary learning.

Recently, low-dose computed tomography (CT) has become highly desirable due to the increasing attent...

Recognition of Lung Adenocarcinoma-specific Gene Pairs Based on Genetic Algorithm and Establishment of a Deep Learning Prediction Model.

AIM AND OBJECTIVE: Lung cancer is a disease with a dismal prognosis and is the major cause of cancer...

Radiomics with artificial intelligence for precision medicine in radiation therapy.

Recently, the concept of radiomics has emerged from radiation oncology. It is a novel approach for s...