AIMC Topic: Multiple Pulmonary Nodules

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Re: Clinical evaluation of a deep-learning-based computer-aided detection system for the detection of pulmonary nodules in a large teaching hospital.

Clinical radiology Dec 11, 2021
Deep Learning Multiple Pulmonary Nodules Solitary Pulmonary Nodule Hospitals, Teaching Humans Computers
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Clinical evaluation of a deep-learning-based computer-aided detection system for the detection of pulmonary nodules in a large teaching hospital.

Clinical radiology Aug 14, 2021
AIM: To evaluate a deep-learning-based computer-aided detection (DL-CAD) software system for pulmonary nodule detection on computed tomography (CT) images and assess its added value in the clinical practice of a large teaching hospital.
Humans Retrospective Studies Tomography, X-Ray Computed Hospitals, Teaching Male Middle Aged Lung Aged, 80 and over Deep Learning Young Adult Adult Adolescent Sensitivity and Specificity Multiple Pulmonary Nodules Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Female Reproducibility of Results Aged
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Lung nodule detection in chest X-rays using synthetic ground-truth data comparing CNN-based diagnosis to human performance.

Scientific reports Aug 4, 2021
We present a method to generate synthetic thorax radiographs with realistic nodules from CT scans, and a perfect ground truth knowledge. We evaluated the detection performance of nine radiologists and two convolutional neural networks in a reader stu...
Multiple Pulmonary Nodules Solitary Pulmonary Nodule Radiologists Radiographic Image Interpretation, Computer-Assisted Humans Neural Networks, Computer ROC Curve Observer Variation Radiography, Thoracic
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Prediction model for malignant pulmonary nodules based on cfMeDIP-seq and machine learning.

Cancer science Jul 21, 2021
Cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) is a new bisulfite-free technique, which can detect the whole-genome methylation of blood cell-free DNA (cfDNA). Using this technique, we identified differentia...
Male Middle Aged Case-Control Studies Lung Neoplasms Aged, 80 and over Adult Sensitivity and Specificity Immunoprecipitation DNA Methylation Cell-Free Nucleic Acids Multiple Pulmonary Nodules High-Throughput Nucleotide Sequencing Humans Machine Learning Prognosis Female Aged
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Natural Language Processing to Identify Pulmonary Nodules and Extract Nodule Characteristics From Radiology Reports.

Chest Jun 4, 2021
BACKGROUND: There is an urgent need for population-based studies on managing patients with pulmonary nodules.
Documentation Radiography, Thoracic Dimensional Measurement Accuracy Natural Language Processing Radiology Tumor Burden Quality Improvement Multiple Pulmonary Nodules Solitary Pulmonary Nodule Calcinosis Tomography, X-Ray Computed Humans Sensitivity and Specificity Algorithms Lung Lung Neoplasms
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Performance and reading time of lung nodule identification on multidetector CT with or without an artificial intelligence-powered computer-aided detection system.

Clinical radiology May 19, 2021
AIM: To compare the performance and reading time of different readers using automatic artificial intelligence (AI)-powered computer-aided detection (CAD) to detect lung nodules in different reading modes.
Multidetector Computed Tomography Artificial Intelligence Time Retrospective Studies Female Lung Reproducibility of Results Lung Neoplasms Multiple Pulmonary Nodules Humans Radiographic Image Interpretation, Computer-Assisted Sensitivity and Specificity Male Middle Aged
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Deep Learning for Malignancy Risk Estimation of Pulmonary Nodules Detected at Low-Dose Screening CT.

Radiology May 18, 2021
Background Accurate estimation of the malignancy risk of pulmonary nodules at chest CT is crucial for optimizing management in lung cancer screening. Purpose To develop and validate a deep learning (DL) algorithm for malignancy risk estimation of pul...
Humans Retrospective Studies Tomography, X-Ray Computed Risk Assessment Deep Learning Lung Neoplasms Mass Screening Multiple Pulmonary Nodules Solitary Pulmonary Nodule Radiation Dosage
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Proposing a deep learning-based method for improving the diagnostic certainty of pulmonary nodules in CT scan of chest.

European radiology May 6, 2021
OBJECTIVE: To compare the performance of a deep learning (DL)-based method for diagnosing pulmonary nodules compared with radiologists' diagnostic approach in computed tomography (CT) of the chest.
Multiple Pulmonary Nodules Solitary Pulmonary Nodule Humans Tomography, X-Ray Computed Deep Learning Lung Neoplasms
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Development and validation of a clinically applicable deep learning strategy (HONORS) for pulmonary nodule classification at CT: A retrospective multicentre study.

Lung cancer (Amsterdam, Netherlands) Mar 11, 2021
PURPOSE: To propose a practical strategy for the clinical application of deep learning algorithm, i.e., Hierarchical-Ordered Network-ORiented Strategy (HONORS), and a new approach to pulmonary nodule classification in various clinical scenarios, i.e....
Humans Lung Neoplasms Retrospective Studies Multiple Pulmonary Nodules Tomography, X-Ray Computed Solitary Pulmonary Nodule Deep Learning
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Development and Validation of Machine Learning-based Model for the Prediction of Malignancy in Multiple Pulmonary Nodules: Analysis from Multicentric Cohorts.

Clinical cancer research : an official journal of the American Association for Cancer Research Feb 24, 2021
PURPOSE: Nodule evaluation is challenging and critical to diagnose multiple pulmonary nodules (MPNs). We aimed to develop and validate a machine learning-based model to estimate the malignant probability of MPNs to guide decision-making.
Aged, 80 and over ROC Curve Young Adult Tomography, X-Ray Computed Adult Humans Lung Neoplasms Clinical Decision-Making Middle Aged Male Female Machine Learning Multiple Pulmonary Nodules Risk Assessment Aged Prospective Studies Lung Adolescent
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