AIMC Topic: Lung Neoplasms

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Diagnosis of Brain Metastases from Lung Cancer Using a Modified Electromagnetism like Mechanism Algorithm.

Journal of medical systems Nov 14, 2015
Brain metastases are commonly found in patients that are diagnosed with primary malignancy on their lung. Lung cancer patients with brain metastasis tend to have a poor survivability, which is less than 6 months in median. Therefore, an early and eff...
Male Middle Aged Lung Neoplasms Support Vector Machine Taiwan Humans Algorithms Female Aged Brain Neoplasms
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Machine Learning Approaches for Predicting Radiation Therapy Outcomes: A Clinician's Perspective.

International journal of radiation oncology, biology, physics Nov 11, 2015
Radiation oncology has always been deeply rooted in modeling, from the early days of isoeffect curves to the contemporary Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) initiative. In recent years, medical modeling for both pr...
Radiotherapy Dosage Radiotherapy Esophagitis Radiation Pneumonitis Humans Machine Learning Xerostomia Neural Networks, Computer Prognosis Artificial Intelligence Reproducibility of Results Treatment Outcome Lung Neoplasms Logistic Models Support Vector Machine Models, Statistical Radiation Oncology
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Automatic classification of pulmonary peri-fissural nodules in computed tomography using an ensemble of 2D views and a convolutional neural network out-of-the-box.

Medical image analysis Sep 8, 2015
In this paper, we tackle the problem of automatic classification of pulmonary peri-fissural nodules (PFNs). The classification problem is formulated as a machine learning approach, where detected nodule candidates are classified as PFNs or non-PFNs. ...
Humans Neural Networks, Computer Software Radiographic Image Enhancement Subtraction Technique Imaging, Three-Dimensional Lung Neoplasms Solitary Pulmonary Nodule Algorithms Radiographic Image Interpretation, Computer-Assisted Pattern Recognition, Automated Tomography, X-Ray Computed Reproducibility of Results Sensitivity and Specificity
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Machine Learning methods for Quantitative Radiomic Biomarkers.

Scientific reports Aug 17, 2015
Radiomics extracts and mines large number of medical imaging features quantifying tumor phenotypic characteristics. Highly accurate and reliable machine-learning approaches can drive the success of radiomic applications in clinical care. In this radi...
Humans Machine Learning Area Under Curve Survival Analysis Tomography, X-Ray Computed Biomarkers, Tumor ROC Curve Lung Neoplasms Carcinoma, Non-Small-Cell Lung
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Robotic radiosurgery system patient-specific QA for extracranial treatments using the planar ion chamber array and the cylindrical diode array.

Journal of applied clinical medical physics Jul 8, 2015
Robotic radiosurgery system has been increasingly employed for extracranial treatments. This work is aimed to study the feasibility of a cylindrical diode array and a planar ion chamber array for patient-specific QA with this robotic radiosurgery sys...
Phantoms, Imaging Radiometry Radiotherapy Setup Errors Radiotherapy Dosage Radiotherapy, Intensity-Modulated Radiosurgery Monte Carlo Method Humans Algorithms Lung Neoplasms Robotics Radiotherapy Planning, Computer-Assisted Quality Assurance, Health Care
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Differential diagnosis of pleural mesothelioma using Logic Learning Machine.

BMC bioinformatics Jun 1, 2015
BACKGROUND: Tumour markers are standard tools for the differential diagnosis of cancer. However, the occurrence of nonspecific symptoms and different malignancies involving the same cancer site may lead to a high proportion of misclassifications. Cla...
Decision Trees Biomarkers, Tumor Humans Neoplasm Metastasis Diagnosis, Differential Male Neural Networks, Computer Logic Mesothelioma Artificial Intelligence Middle Aged Mesothelioma, Malignant Female Cohort Studies Pleural Neoplasms Lung Neoplasms
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Bioinformatics approach reveals systematic mechanism underlying lung adenocarcinoma.

Tumori May 21, 2015
BACKGROUND: The purpose of this work was to explore the systematic molecular mechanism of lung adenocarcinoma and gain a deeper insight into it.
Adenocarcinoma of Lung Computational Biology Collagen Type X Gene Expression Regulation, Neoplastic Receptor Cross-Talk Membrane Proteins Humans Signal Transduction Calcium Software Adenocarcinoma Gene Expression Profiling Peroxisome Proliferator-Activated Receptors Lung Neoplasms Protein Array Analysis Gene Ontology
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Cancer adjuvant chemotherapy strategic classification by artificial neural network with gene expression data: An example for non-small cell lung cancer.

Journal of biomedical informatics May 18, 2015
PURPOSE: Adjuvant chemotherapy (ACT) is used after surgery to prevent recurrence or metastases. However, ACT for non-small cell lung cancer (NSCLC) is still controversial. This study aimed to develop prediction models to distinguish who is suitable f...
Machine Learning Algorithms Prognosis Female Reproducibility of Results Aged Male Middle Aged Gene Expression Profiling Neoplasm Recurrence, Local Lung Neoplasms Computational Biology Neoplasm Metastasis Humans Gene Expression Regulation, Neoplastic Proportional Hazards Models Neural Networks, Computer Treatment Outcome Kaplan-Meier Estimate Carcinoma, Non-Small-Cell Lung Chemotherapy, Adjuvant
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Application of an artificial neural network model for selection of potential lung cancer biomarkers.

Journal of breath research May 6, 2015
Determination of volatile organic compounds (VOCs) in the exhaled breath samples of lung cancer patients and healthy controls was carried out by SPME-GC/MS (solid phase microextraction- gas chromatography combined with mass spectrometry) analyses. In...
Solid Phase Microextraction Breath Tests Exhalation Small Cell Lung Carcinoma Carcinoma, Non-Small-Cell Lung Humans Neural Networks, Computer Mass Spectrometry Female Gas Chromatography-Mass Spectrometry Young Adult Aged Middle Aged Volatile Organic Compounds Aged, 80 and over Adult Case-Control Studies Smoking Sensitivity and Specificity Lung Neoplasms Biomarkers, Tumor Adenocarcinoma Male
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Computer-aided lung nodule recognition by SVM classifier based on combination of random undersampling and SMOTE.

Computational and mathematical methods in medicine Apr 6, 2015
In lung cancer computer-aided detection/diagnosis (CAD) systems, classification of regions of interest (ROI) is often used to detect/diagnose lung nodule accurately. However, problems of unbalanced datasets often have detrimental effects on the perfo...
Support Vector Machine Cluster Analysis Solitary Pulmonary Nodule Humans Models, Statistical Pattern Recognition, Automated Reproducibility of Results Radiographic Image Interpretation, Computer-Assisted Algorithms Diagnosis, Computer-Assisted Imaging, Three-Dimensional Tomography, X-Ray Computed Lung Neoplasms
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