AIMC Topic: Lung Neoplasms

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Design and application of tumor prediction model based on statistical method.

Computer assisted surgery (Abingdon, England)
Two prediction models for tumor prediction based on logistic regression and BP neural network were proposed in this paper; a sensitivity analysis of risk factors was also conducted. The two protocols will be implemented in the R language and demonstr...

A prediction model for early death in non-small cell lung cancer patients following curative-intent chemoradiotherapy.

Acta oncologica (Stockholm, Sweden)
BACKGROUND: Early death after a treatment can be seen as a therapeutic failure. Accurate prediction of patients at risk for early mortality is crucial to avoid unnecessary harm and reducing costs. The goal of our work is two-fold: first, to evaluate ...

Low-Dose Lung CT Image Restoration Using Adaptive Prior Features From Full-Dose Training Database.

IEEE transactions on medical imaging
The valuable structure features in full-dose computed tomography (FdCT) scans can be exploited as prior knowledge for low-dose CT (LdCT) imaging. However, lacking the capability to represent local characteristics of interested structures of the LdCT ...

Prediction of lung cancer patient survival via supervised machine learning classification techniques.

International journal of medical informatics
Outcomes for cancer patients have been previously estimated by applying various machine learning techniques to large datasets such as the Surveillance, Epidemiology, and End Results (SEER) program database. In particular for lung cancer, it is not we...

Impact of pixel-based machine-learning techniques on automated frameworks for delineation of gross tumor volume regions for stereotactic body radiation therapy.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
The aim of this study was to investigate the impact of pixel-based machine learning (ML) techniques, i.e., fuzzy-c-means clustering method (FCM), and the artificial neural network (ANN) and support vector machine (SVM), on an automated framework for ...

Automatic Categorization and Scoring of Solid, Part-Solid and Non-Solid Pulmonary Nodules in CT Images with Convolutional Neural Network.

Scientific reports
We present a computer-aided diagnosis system (CADx) for the automatic categorization of solid, part-solid and non-solid nodules in pulmonary computerized tomography images using a Convolutional Neural Network (CNN). Provided with only a two-dimension...

Detection of lung cancer in exhaled breath with an electronic nose using support vector machine analysis.

Journal of breath research
Lung cancer is one of the most common malignancies and has a low 5-year survival rate. There are no cheap, simple and widely available screening methods for the early diagnostics of lung cancer. The aim of this study was to determine whether analysis...

Using Deep Learning for Classification of Lung Nodules on Computed Tomography Images.

Journal of healthcare engineering
Lung cancer is the most common cancer that cannot be ignored and cause death with late health care. Currently, CT can be used to help doctors detect the lung cancer in the early stages. In many cases, the diagnosis of identifying the lung cancer depe...