AIMC Topic: Lung Neoplasms

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A Two-Stage Convolutional Neural Networks for Lung Nodule Detection.

IEEE journal of biomedical and health informatics Jan 3, 2020
Early detection of lung cancer is an effective way to improve the survival rate of patients. It is a critical step to have accurate detection of lung nodules in computed tomography (CT) images for the diagnosis of lung cancer. However, due to the het...
Tomography, X-Ray Computed Humans Imaging, Three-Dimensional Neural Networks, Computer Lung Neoplasms Radiographic Image Interpretation, Computer-Assisted
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Test-retest reproducibility of a deep learning-based automatic detection algorithm for the chest radiograph.

European radiology Jan 3, 2020
OBJECTIVES: To perform test-retest reproducibility analyses for deep learning-based automatic detection algorithm (DLAD) using two stationary chest radiographs (CRs) with short-term intervals, to analyze influential factors on test-retest variations,...
Pneumonectomy Radiography, Thoracic Deep Learning Lung Neoplasms Humans Reproducibility of Results Multiple Pulmonary Nodules Algorithms Aged Radiographic Image Interpretation, Computer-Assisted Retrospective Studies Male Female Middle Aged
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Distributed learning on 20 000+ lung cancer patients - The Personal Health Train.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Jan 3, 2020
BACKGROUND AND PURPOSE: Access to healthcare data is indispensable for scientific progress and innovation. Sharing healthcare data is time-consuming and notoriously difficult due to privacy and regulatory concerns. The Personal Health Train (PHT) pro...
Humans Machine Learning Algorithms China Lung Neoplasms Privacy
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AI-based computer-aided diagnosis (AI-CAD): the latest review to read first.

Radiological physics and technology Jan 2, 2020
The third artificial intelligence (AI) boom is coming, and there is an inkling that the speed of its evolution is quickly increasing. In games like chess, shogi, and go, AI has already defeated human champions, and the fact that it is able to achieve...
Humans Artificial Intelligence Deep Learning Image Processing, Computer-Assisted Lung Neoplasms Stroke Machine Learning Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Neoplasms Diagnosis, Computer-Assisted
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Single-stage posterior total en bloc spondylectomy in the treatment of lumbar spinal metastases.

Clinical neurology and neurosurgery Dec 20, 2019
OBJECTIVE: To report the clinical and radiographic outcomes of single-stage posterior total en bloc spondylectomy (TES) of lumbar spinal metastases.
Rectal Neoplasms Surgical Wound Infection Kidney Neoplasms Postoperative Complications Low Back Pain Length of Stay Metastasectomy Plastic Surgery Procedures Blood Loss, Surgical Liver Neoplasms Adult Psoas Muscles Prostatic Neoplasms Operative Time Lung Neoplasms Biomechanical Phenomena Neurosurgical Procedures Spinal Neoplasms Cerebrospinal Fluid Leak Humans Male Lumbar Vertebrae Spinal Nerve Roots Pain Measurement Middle Aged Retrospective Studies Female Aged
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Multi-objective ensemble deep learning using electronic health records to predict outcomes after lung cancer radiotherapy.

Physics in medicine and biology Dec 13, 2019
Accurately predicting treatment outcome is crucial for creating personalized treatment plans and follow-up schedules. Electronic health records (EHRs) contain valuable patient-specific information that can be leveraged to improve outcome prediction. ...
Humans Carcinoma, Bronchogenic Electronic Health Records Deep Learning Lung Neoplasms Treatment Outcome
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Shape and margin-aware lung nodule classification in low-dose CT images via soft activation mapping.

Medical image analysis Dec 12, 2019
A number of studies on lung nodule classification lack clinical/biological interpretations of the features extracted by convolutional neural network (CNN). The methods like class activation mapping (CAM) and gradient-based CAM (Grad-CAM) are tailored...
Lung Neoplasms Humans Neural Networks, Computer Solitary Pulmonary Nodule Tomography, X-Ray Computed Radiographic Image Interpretation, Computer-Assisted Sensitivity and Specificity
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Artificial intelligence applications for thoracic imaging.

European journal of radiology Dec 11, 2019
Artificial intelligence is a hot topic in medical imaging. The development of deep learning methods and in particular the use of convolutional neural networks (CNNs), have led to substantial performance gain over the classic machine learning techniqu...
Lung Neoplasms Early Detection of Cancer Radiologists Radiography, Thoracic Thorax Artificial Intelligence Machine Learning Algorithms Deep Learning Humans
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Artificial intelligence for detecting small FDG-positive lung nodules in digital PET/CT: impact of image reconstructions on diagnostic performance.

European radiology Dec 10, 2019
OBJECTIVES: To evaluate the diagnostic performance of a deep learning algorithm for automated detection of small F-FDG-avid pulmonary nodules in PET scans, and to assess whether novel block sequential regularized expectation maximization (BSREM) reco...
Humans Artificial Intelligence Algorithms Deep Learning Image Processing, Computer-Assisted Lung Neoplasms Radiopharmaceuticals Multiple Pulmonary Nodules Retrospective Studies Adult Solitary Pulmonary Nodule Fluorodeoxyglucose F18 Female Sensitivity and Specificity Positron Emission Tomography Computed Tomography Aged Male Aged, 80 and over Middle Aged
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A deep residual learning network for predicting lung adenocarcinoma manifesting as ground-glass nodule on CT images.

European radiology Dec 6, 2019
OBJECTIVE: To develop a deep learning-based artificial intelligence (AI) scheme for predicting the likelihood of the ground-glass nodule (GGN) detected on CT images being invasive adenocarcinoma (IA) and also compare the accuracy of this AI scheme wi...
Feasibility Studies Adenocarcinoma of Lung Adenocarcinoma in Situ Lung Neoplasms Solitary Pulmonary Nodule Neoplasm Invasiveness Radiologists Adult Male Middle Aged Disease Progression Deep Learning Adolescent ROC Curve Image Processing, Computer-Assisted Female Aged Aged, 80 and over Young Adult Neural Networks, Computer Artificial Intelligence Retrospective Studies Tomography, X-Ray Computed Humans
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