AIMC Topic: Lung Neoplasms

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Radiogenomic Models Using Machine Learning Techniques to Predict EGFR Mutations in Non-Small Cell Lung Cancer.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes Feb 17, 2020
BACKGROUND: The purpose of this study was to build radiogenomics models from texture signatures derived from computed tomography (CT) and F-FDG PET-CT (FDG PET-CT) images of non-small cell lung cancer (NSCLC) with and without epidermal growth factor ...
Machine Learning Retrospective Studies Female Reproducibility of Results Aged Sensitivity and Specificity Male Lung Humans Positron Emission Tomography Computed Tomography Mutation Lung Neoplasms Radiopharmaceuticals Carcinoma, Non-Small-Cell Lung Image Interpretation, Computer-Assisted Fluorodeoxyglucose F18 Predictive Value of Tests ErbB Receptors Imaging Genomics
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Comparison of medium-term survival outcomes between robot-assisted thoracoscopic surgery and video-assisted thoracoscopic surgery in treating primary lung cancer.

General thoracic and cardiovascular surgery Feb 13, 2020
OBJECTIVES: Robot-assisted thoracoscopic surgery (RATS) for primary lung cancer has been spreading rapidly in Japan. While RATS has various technical advantages over video-assisted thoracoscopic surgery (VATS), the quality of surgery from an oncologi...
Operative Time Robotics Pneumonectomy Thoracic Surgery, Video-Assisted Humans Middle Aged Japan Prognosis Time Factors Adult Postoperative Period Female Lung Neoplasms Survival Rate Aged Propensity Score Follow-Up Studies Male Aged, 80 and over
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Prognostic value of anthropometric measures extracted from whole-body CT using deep learning in patients with non-small-cell lung cancer.

European radiology Feb 13, 2020
INTRODUCTION: The aim of the study was to extract anthropometric measures from CT by deep learning and to evaluate their prognostic value in patients with non-small-cell lung cancer (NSCLC).
Aged Adult Survival Rate Male Prognosis Female Reproducibility of Results Carcinoma, Non-Small-Cell Lung Muscle, Skeletal Positron Emission Tomography Computed Tomography Neoplasm Staging Middle Aged Disease Progression Deep Learning Lung Neoplasms Humans Body Surface Area Intra-Abdominal Fat Subcutaneous Fat Body Composition Whole Body Imaging Progression-Free Survival Proportional Hazards Models
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CT-based deep learning model to differentiate invasive pulmonary adenocarcinomas appearing as subsolid nodules among surgical candidates: comparison of the diagnostic performance with a size-based logistic model and radiologists.

European radiology Feb 13, 2020
OBJECTIVES: To evaluate the deep learning models for differentiating invasive pulmonary adenocarcinomas (IACs) among subsolid nodules (SSNs) considered for resection in a retrospective diagnostic cohort in comparison with a size-based logistic model ...
Radiologists Radiography, Thoracic Adenocarcinoma of Lung ROC Curve Lung Neoplasms Logistic Models Humans Retrospective Studies Tomography, X-Ray Computed Female Aged Male Middle Aged Deep Learning
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Short Keynote Paper: Mainstreaming Personalized Healthcare-Transforming Healthcare Through New Era of Artificial Intelligence.

IEEE journal of biomedical and health informatics Feb 10, 2020
Medicine has entered the digital era, driven by data from new modalities, especially genomics and imaging, as well as new sources such as wearables and Internet of Things. As we gain a deeper understanding of the disease biology and how diseases affe...
Humans Sepsis Lung Neoplasms Genomics Artificial Intelligence Medical Informatics Algorithms Precision Medicine Deep Learning
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Technical Note: 3D localization of lung tumors on cone beam CT projections via a convolutional recurrent neural network.

Medical physics Jan 28, 2020
PURPOSE: To design a convolutional recurrent neural network (CRNN) that calculates three-dimensional (3D) positions of lung tumors from continuously acquired cone beam computed tomography (CBCT) projections, and facilitates the sorting and reconstruc...
Lung Neoplasms Humans Neural Networks, Computer Cone-Beam Computed Tomography Imaging, Three-Dimensional
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The Emerging Role of Radiomics in COPD and Lung Cancer.

Respiration; international review of thoracic diseases Jan 28, 2020
Medical imaging plays a key role in evaluating and monitoring lung diseases such as chronic obstructive pulmonary disease (COPD) and lung cancer. The application of artificial intelligence in medical imaging has transformed medical images into mineab...
Pulmonary Disease, Chronic Obstructive Decision Support Systems, Clinical Image Processing, Computer-Assisted Lung Neoplasms Artificial Intelligence Machine Learning Prognosis Humans Treatment Outcome Neoplasm Staging Workflow Data Mining
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Commentary: Robot-assisted segmentectomy is safe and expensive-What is the debate?

The Journal of thoracic and cardiovascular surgery Jan 25, 2020
Humans Robotics Robotic Surgical Procedures Lung Neoplasms Propensity Score
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A multi-scale framework with unsupervised joint training of convolutional neural networks for pulmonary deformable image registration.

Physics in medicine and biology Jan 13, 2020
To achieve accurate and fast deformable image registration (DIR) for pulmonary CT, we proposed a Multi-scale DIR framework with unsupervised Joint training of Convolutional Neural Network (MJ-CNN). MJ-CNN contains three models at multi-scale levels f...
Image Processing, Computer-Assisted Lung Neoplasms Humans Four-Dimensional Computed Tomography Neural Networks, Computer
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An effective approach for CT lung segmentation using mask region-based convolutional neural networks.

Artificial intelligence in medicine Jan 8, 2020
Computer vision systems have numerous tools to assist in various medical fields, notably in image diagnosis. Computed tomography (CT) is the principal imaging method used to assist in the diagnosis of diseases such as bone fractures, lung cancer, hea...
Tomography, X-Ray Computed Humans Support Vector Machine Lung Neural Networks, Computer Bayes Theorem Image Processing, Computer-Assisted Machine Learning Lung Neoplasms
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