AIMC Topic: Lung Neoplasms

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Using machine learning to predict radiation pneumonitis in patients with stage I non-small cell lung cancer treated with stereotactic body radiation therapy.

Physics in medicine and biology Jul 27, 2016
To develop a patient-specific 'big data' clinical decision tool to predict pneumonitis in stage I non-small cell lung cancer (NSCLC) patients after stereotactic body radiation therapy (SBRT). 61 features were recorded for 201 consecutive patients wit...
Middle Aged Lung Neoplasms Carcinoma, Non-Small-Cell Lung Multivariate Analysis Aged Aged, 80 and over Male Radiosurgery Radiation Pneumonitis Humans Machine Learning Algorithms Female Reproducibility of Results
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Automatic weighing attribute to retrieve similar lung cancer nodules.

BMC medical informatics and decision making Jul 21, 2016
BACKGROUND: Cancer is a disease characterized as an uncontrolled growth of abnormal cells that invades neighboring tissues and destroys them. Lung cancer is the primary cause of cancer-related deaths in the world, and it diagnosis is a complex task f...
Diagnosis, Computer-Assisted Lung Neoplasms Image Interpretation, Computer-Assisted Pattern Recognition, Automated Humans Machine Learning
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Fuzzy Clustering Applied to ROI Detection in Helical Thoracic CT Scans with a New Proposal and Variants.

BioMed research international Jul 18, 2016
The detection of pulmonary nodules is one of the most studied problems in the field of medical image analysis due to the great difficulty in the early detection of such nodules and their social impact. The traditional approach involves the developmen...
Pattern Recognition, Automated Humans Radiography, Thoracic Sensitivity and Specificity Algorithms Tomography, Spiral Computed Lung Neoplasms Reproducibility of Results Fuzzy Logic Solitary Pulmonary Nodule
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Incidence, Results, and Our Current Intraoperative Technique to Control Major Vascular Injuries During Minimally Invasive Robotic Thoracic Surgery.

The Annals of thoracic surgery Jun 22, 2016
BACKGROUND: Our objective is to report our incidence, results, and technique for the control of major vascular injuries during minimally invasive robotic thoracic surgery.
Humans Retrospective Studies Female Aged Follow-Up Studies Robotics Pneumonectomy Thoracic Surgery, Video-Assisted Male Incidence Lung Neoplasms Treatment Outcome Intraoperative Complications Alabama Vascular System Injuries
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Lung Cancer Detection Using Fuzzy Auto-Seed Cluster Means Morphological Segmentation and SVM Classifier.

Journal of medical systems Jun 14, 2016
An effective fuzzy auto-seed cluster means morphological algorithm developed in this work to segment the lung nodules from the consecutive slices of Computer Tomography (CT) images to detect the lung cancer. The initial cluster values were chosen aut...
Lung Neoplasms Support Vector Machine Fuzzy Logic Humans Tomography, X-Ray Computed Sensitivity and Specificity Image Processing, Computer-Assisted
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A dosimetric comparison of real-time adaptive and non-adaptive radiotherapy: A multi-institutional study encompassing robotic, gimbaled, multileaf collimator and couch tracking.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Mar 22, 2016
PURPOSE: A study of real-time adaptive radiotherapy systems was performed to test the hypothesis that, across delivery systems and institutions, the dosimetric accuracy is improved with adaptive treatments over non-adaptive radiotherapy in the presen...
Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Movement Humans Male Computer Systems Lung Neoplasms Robotics Prostatic Neoplasms
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SNRFCB: sub-network based random forest classifier for predicting chemotherapy benefit on survival for cancer treatment.

Molecular bioSystems Feb 11, 2016
Adjuvant chemotherapy (CTX) should be individualized to provide potential survival benefit and avoid potential harm to cancer patients. Our goal was to establish a computational approach for making personalized estimates of the survival benefit from ...
Chemotherapy, Adjuvant Support Vector Machine Models, Statistical Area Under Curve Machine Learning Kaplan-Meier Estimate Prognosis Lung Neoplasms Female Computational Biology Reproducibility of Results Treatment Outcome Breast Neoplasms Male Neoplasms Antineoplastic Agents Humans Neural Networks, Computer
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Advances in Uniportal Video-Assisted Thoracoscopic Surgery: Pushing the Envelope.

Thoracic surgery clinics Feb 10, 2016
Uniportal video-assisted thoracic surgery (VATS) represents a radical change in the approach to lung resection compared with conventional VATS. Because the placement of the surgical instruments and the camera is done through the same incision, unipor...
Pneumonectomy Thoracic Surgery, Video-Assisted Humans Lung Neoplasms Robotics
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Use and Outcomes of Minimally Invasive Lobectomy for Stage I Non-Small Cell Lung Cancer in the National Cancer Data Base.

The Annals of thoracic surgery Jan 26, 2016
BACKGROUND: Previous studies have raised concerns that video-assisted thoracoscopic (VATS) lobectomy may compromise nodal evaluation. The advantages or limitations of robotic lobectomy have not been thoroughly evaluated.
Puerto Rico Incidence Lung Neoplasms United States Treatment Outcome Humans Retrospective Studies Survival Rate Female Registries Carcinoma, Non-Small-Cell Lung Male Aged Pneumonectomy Follow-Up Studies Postoperative Complications Thoracic Surgery, Video-Assisted Robotics Propensity Score Neoplasm Staging
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Drug repositioning for non-small cell lung cancer by using machine learning algorithms and topological graph theory.

BMC bioinformatics Jan 11, 2016
BACKGROUND: Non-small cell lung cancer (NSCLC) is one of the leading causes of death globally, and research into NSCLC has been accumulating steadily over several years. Drug repositioning is the current trend in the pharmaceutical industry for ident...
Gene Expression Regulation, Neoplastic Signal Transduction Models, Theoretical Carcinoma, Non-Small-Cell Lung Neoplasm Proteins Algorithms Drug Repositioning Drug Discovery Microarray Analysis Antineoplastic Agents Lung Neoplasms Humans Machine Learning
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