AIMC Topic: Lung Neoplasms

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A preliminary study of a photon dose calculation algorithm using a convolutional neural network.

Physics in medicine and biology
The aim of dose calculation algorithm research is to improve the calculation accuracy while maximizing the calculation efficiency. In this study, the three-dimensional distribution of total energy release per unit mass (TERMA) and the electron densit...

Combination of Deep Learning-Based Denoising and Iterative Reconstruction for Ultra-Low-Dose CT of the Chest: Image Quality and Lung-RADS Evaluation.

AJR. American journal of roentgenology
The objective of our study was to assess the effect of the combination of deep learning-based denoising (DLD) and iterative reconstruction (IR) on image quality and Lung Imaging Reporting and Data System (Lung-RADS) evaluation on chest ultra-low-dos...

Verification of the machine delivery parameters of a treatment plan via deep learning.

Physics in medicine and biology
We developed a generative adversarial network (GAN)-based deep learning approach to estimate the multileaf collimator (MLC) aperture and corresponding monitor units (MUs) from a given 3D dose distribution. The proposed design of the adversarial netwo...

Multi-view radiomics and dosiomics analysis with machine learning for predicting acute-phase weight loss in lung cancer patients treated with radiotherapy.

Physics in medicine and biology
We propose a multi-view data analysis approach using radiomics and dosiomics (R&D) texture features for predicting acute-phase weight loss (WL) in lung cancer radiotherapy. Baseline weight of 388 patients who underwent intensity modulated radiation t...

Performance of a Deep Learning Algorithm Compared with Radiologic Interpretation for Lung Cancer Detection on Chest Radiographs in a Health Screening Population.

Radiology
Background The performance of a deep learning algorithm for lung cancer detection on chest radiographs in a health screening population is unknown. Purpose To validate a commercially available deep learning algorithm for lung cancer detection on ches...

Multi-scale supervised clustering-based feature selection for tumor classification and identification of biomarkers and targets on genomic data.

BMC genomics
BACKGROUND: The small number of samples and the curse of dimensionality hamper the better application of deep learning techniques for disease classification. Additionally, the performance of clustering-based feature selection algorithms is still far ...

Deep Learning to Estimate RECIST in Patients with NSCLC Treated with PD-1 Blockade.

Cancer discovery
Real-world evidence (RWE), conclusions derived from analysis of patients not treated in clinical trials, is increasingly recognized as an opportunity for discovery, to reduce disparities, and to contribute to regulatory approval. Maximal value of RWE...

Deep Learning Using Chest Radiographs to Identify High-Risk Smokers for Lung Cancer Screening Computed Tomography: Development and Validation of a Prediction Model.

Annals of internal medicine
BACKGROUND: Lung cancer screening with chest computed tomography (CT) reduces lung cancer death. Centers for Medicare & Medicaid Services (CMS) eligibility criteria for lung cancer screening with CT require detailed smoking information and miss many ...