AIMC Topic: Lung Neoplasms

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CNN models discriminating between pulmonary micro-nodules and non-nodules from CT images.

Biomedical engineering online Jul 16, 2018
BACKGROUND: Early and automatic detection of pulmonary nodules from CT lung screening is the prerequisite for precise management of lung cancer. However, a large number of false positives appear in order to increase the sensitivity, especially for de...
Lung Neoplasms False Positive Reactions Humans Tomography, X-Ray Computed Lung Neural Networks, Computer Image Processing, Computer-Assisted Databases, Factual
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Exploratory analysis using machine learning to predict for chest wall pain in patients with stage I non-small-cell lung cancer treated with stereotactic body radiation therapy.

Journal of applied clinical medical physics Jul 10, 2018
BACKGROUND AND PURPOSE: Chest wall toxicity is observed after stereotactic body radiation therapy (SBRT) for peripherally located lung tumors. We utilize machine learning algorithms to identify toxicity predictors to develop dose-volume constraints.
Humans Activities of Daily Living Radiosurgery Thoracic Wall Machine Learning Lung Neoplasms Carcinoma, Non-Small-Cell Lung
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[Not Available].

Zentralblatt fur Chirurgie Jun 22, 2018
Robotic Surgical Procedures Bronchi Lung Neoplasms Carcinoma, Non-Small-Cell Lung Robotics Humans
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The utilisation of convolutional neural networks in detecting pulmonary nodules: a review.

The British journal of radiology Jun 19, 2018
Lung cancer is one of the leading causes of cancer-related fatality in the world. Patients display few or even no signs or symptoms in the early stages, resulting in up to 75% of patients diagnosed in the later stages of the disease. Consequently, th...
Lung Neoplasms Humans Solitary Pulmonary Nodule Neural Networks, Computer Early Detection of Cancer Tomography, X-Ray Computed
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Adaptive multinomial regression with overlapping groups for multi-class classification of lung cancer.

Computers in biology and medicine Jun 19, 2018
Multi-class classification has attracted much attention in cancer diagnosis and treatment and many machine learning methods have emerged for addressing this issue recently. However, class imbalance and gene selection problems occur in classifying lun...
Humans Machine Learning Algorithms Lung Neoplasms Models, Biological
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Automatic recognition of 3D GGO CT imaging signs through the fusion of hybrid resampling and layer-wise fine-tuning CNNs.

Medical & biological engineering & computing Jun 6, 2018
Ground-glass opacity (GGO) is a common CT imaging sign on high-resolution CT, which means the lesion is more likely to be malignant compared to common solid lung nodules. The automatic recognition of GGO CT imaging signs is of great importance for ea...
Humans Sensitivity and Specificity Lung Imaging, Three-Dimensional Neural Networks, Computer Algorithms Tomography, X-Ray Computed Lung Neoplasms Image Interpretation, Computer-Assisted
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Profiling Lung Cancer Patients Using Electronic Health Records.

Journal of medical systems May 31, 2018
If Electronic Health Records contain a large amount of information about the patient's condition and response to treatment, which can potentially revolutionize the clinical practice, such information is seldom considered due to the complexity of its ...
Humans Electronic Health Records Natural Language Processing Female Data Mining Reproducibility of Results Male Lung Neoplasms
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Evolutionary image simplification for lung nodule classification with convolutional neural networks.

International journal of computer assisted radiology and surgery May 29, 2018
PURPOSE: Understanding decisions of deep learning techniques is important. Especially in the medical field, the reasons for a decision in a classification task are as crucial as the pure classification results. In this article, we propose a new appro...
Solitary Pulmonary Nodule Decision Making Electronic Data Processing Neural Networks, Computer Image Processing, Computer-Assisted Machine Learning Lung Neoplasms Algorithms Software Humans Lung Diagnosis, Computer-Assisted
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Small lung nodules detection based on local variance analysis and probabilistic neural network.

Computer methods and programs in biomedicine Apr 28, 2018
BACKGROUND AND OBJECTIVE: In medical examinations doctors use various techniques in order to provide to the patients an accurate analysis of their actual state of health. One of the commonly used methodologies is the x-ray screening. This examination...
X-Rays Neural Networks, Computer Radiographic Image Enhancement Algorithms Probability Medical Errors Radiographic Image Interpretation, Computer-Assisted Databases, Factual Pattern Recognition, Automated Image Processing, Computer-Assisted Carcinoma Reproducibility of Results False Positive Reactions Lung Neoplasms Humans Sensitivity and Specificity Solitary Pulmonary Nodule Lung
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Computer-aided diagnosis of lung nodule using gradient tree boosting and Bayesian optimization.

PloS one Apr 19, 2018
We aimed to evaluate a computer-aided diagnosis (CADx) system for lung nodule classification focussing on (i) usefulness of the conventional CADx system (hand-crafted imaging feature + machine learning algorithm), (ii) comparison between support vect...
Area Under Curve Bayes Theorem Diagnosis, Computer-Assisted Algorithms Lung Neoplasms Humans ROC Curve Databases, Factual Support Vector Machine Machine Learning Image Processing, Computer-Assisted Tomography, X-Ray Computed Solitary Pulmonary Nodule
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