AIMC Topic: Lung Neoplasms

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Swarm Intelligence-Enhanced Detection of Non-Small-Cell Lung Cancer Using Tumor-Educated Platelets.

Cancer cell Aug 14, 2017
Blood-based liquid biopsies, including tumor-educated blood platelets (TEPs), have emerged as promising biomarker sources for non-invasive detection of cancer. Here we demonstrate that particle-swarm optimization (PSO)-enhanced algorithms enable effi...
Biomarkers, Tumor Male Middle Aged Gene Expression Profiling Aged Aged, 80 and over Adult Support Vector Machine Carcinoma, Non-Small-Cell Lung High-Throughput Nucleotide Sequencing Blood Platelets Diagnosis, Computer-Assisted Humans Cohort Studies Artificial Intelligence Lung Neoplasms Algorithms Inflammation Female
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Predictive Analytics through Machine Learning in the clinical settings.

Computer methods and programs in biomedicine Jun 1, 2017
Humans Machine Learning Decision Support Techniques Image Interpretation, Computer-Assisted Diagnosis, Computer-Assisted Prognosis Electrophysiological Phenomena Decision Support Systems, Clinical Labor Onset Pregnancy Lung Neoplasms Computational Biology Female
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Unity is Strength: Improving biomedical classification performance based on ensemble learning approaches.

Computer methods and programs in biomedicine Apr 1, 2017
Lung Neoplasms Humans Computational Biology Tomography, X-Ray Computed Electroencephalography Algorithms Image Interpretation, Computer-Assisted Diagnosis, Computer-Assisted Supervised Machine Learning Autistic Disorder Decision Support Systems, Clinical
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The Diagnostic Imagination in Radiology: Part 2.

Radiology management Mar 1, 2017
Developing algorithms for the improve- ment of diagnostic care leverages tech- nologies and techniques developed across industries that are exponentially being improved, developed, and tested. Machine learning means extracting patterns not only from ...
Algorithms Lung Neoplasms Diagnosis, Differential Humans Diagnostic Imaging Image Interpretation, Computer-Assisted Machine Learning
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Development of Asian Non-Small Cell Lung Cancer Survival Prediction Model Using an Innovative Method of Bayesian Network.

Studies in health technology and informatics Jan 1, 2017
We constructed a novel prognostic model using an innovative method of Bayesian Network (BN) to predict Non-Small Cell Lung Cancer survival status within 5 years after operation in the Asian population. The proposed BN model could present the relation...
Lung Neoplasms Humans Carcinoma, Non-Small-Cell Lung Algorithms Bayes Theorem Prognosis Asian People
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KAI1/CD82, Metastasis Suppressor Gene as a Therapeutic Target for Non-Small-Cell Lung Carcinoma.

Journal of environmental pathology, toxicology and oncology : official organ of the International Society for Environmental Toxicology and Cancer Jan 1, 2017
Lung cancer is the most frequent malignancy and the leading cause of cancer-related death worldwide; it is the second most common cancer, comprising 1.69 million deaths worldwide per year. Among these, 85% of lung cancers are non-small-cell lung carc...
Humans Kangai-1 Protein Lung Neoplasms Carcinoma, Non-Small-Cell Lung ErbB Receptors Wnt Signaling Pathway Genes, Tumor Suppressor Genes, p53
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Prediction of pathologic femoral fractures in patients with lung cancer using machine learning algorithms: Comparison of computed tomography-based radiological features with clinical features versus without clinical features.

Journal of orthopaedic surgery (Hong Kong) Jan 1, 2017
PURPOSE: The purpose of this article is to compare the predictive power of two models trained with computed tomography (CT)-based radiological features and both CT-based radiological and clinical features for pathologic femoral fractures in patients ...
Male Middle Aged ROC Curve Lung Neoplasms Risk Factors Aged Adult Femoral Fractures Logistic Models Odds Ratio Fractures, Spontaneous Humans Machine Learning Algorithms Tomography, X-Ray Computed Female
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Similarity measurement of lung masses for medical image retrieval using kernel based semisupervised distance metric.

Medical physics Dec 1, 2016
PURPOSE: To develop a new algorithm to measure the similarity between the query lung mass and reference lung mass data set for content-based medical image retrieval (CBMIR).
Humans Diagnostic Imaging Databases, Factual Supervised Machine Learning Image Processing, Computer-Assisted Lung Neoplasms
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Serum Amyloid P-component Level May be a Biomarker for Lung Toxicities and Overall Survival after Thoracic Radiotherapy for Non-small Cell Lung Cancer.

Clinical laboratory Nov 1, 2016
BACKGROUND: Serum amyloid P-component (SAP) contributes to the clearance of apoptotic cells. As one of the main acute-phase reactants, SAP regulates key aspects of inflammation and sets a threshold for immune cell activation. This study aimed to inve...
Biomarkers, Tumor Time Factors Lung Neoplasms Radiation Pneumonitis Enzyme-Linked Immunosorbent Assay Serum Amyloid P-Component Humans Risk Factors Treatment Outcome Pulmonary Fibrosis Carcinoma, Non-Small-Cell Lung Proportional Hazards Models Predictive Value of Tests Multivariate Analysis Kaplan-Meier Estimate
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Complementary feature selection from alternative splicing events and gene expression for phenotype prediction.

Bioinformatics (Oxford, England) Sep 1, 2016
MOTIVATION: A central task of bioinformatics is to develop sensitive and specific means of providing medical prognoses from biomarker patterns. Common methods to predict phenotypes in RNA-Seq datasets utilize machine learning algorithms trained via g...
Animals Lung Neoplasms Carcinoma, Non-Small-Cell Lung Amyotrophic Lateral Sclerosis Mice, Transgenic Alternative Splicing Machine Learning Algorithms Phenotype Pulmonary Disease, Chronic Obstructive Humans
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