AIMC Topic: Lung

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Effects of Expert-Determined Reference Standards in Evaluating the Diagnostic Performance of a Deep Learning Model: A Malignant Lung Nodule Detection Task on Chest Radiographs.

Korean journal of radiology Feb 1, 2023
OBJECTIVE: Little is known about the effects of using different expert-determined reference standards when evaluating the performance of deep learning-based automatic detection (DLAD) models and their added value to radiologists. We assessed the conc...
Radiography, Thoracic Lung Deep Learning Radiographic Image Interpretation, Computer-Assisted Reference Standards Lung Neoplasms Humans Retrospective Studies Sensitivity and Specificity Artificial Intelligence
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Complex Robotic Lung Resection.

Thoracic surgery clinics Feb 1, 2023
Performing robotic thoracic lung resection is becoming an option for patients with complex thoracic disease. The robotic-assisted approach has similar survival with decreased postoperative pain, morbidity, and hospital length of stay compared with th...
Retrospective Studies Lung Lung Neoplasms Humans Robotic Surgical Procedures Pneumonectomy Treatment Outcome Thoracic Surgery, Video-Assisted Robotics
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Biportal robotic pulmonary lobectomy, initial experience - case report.

Rozhledy v chirurgii : mesicnik Ceskoslovenske chirurgicke spolecnosti Jan 1, 2023
INTRODUCTION: Thanks to perfect visualization and high maneuverability of instruments, the robotic technique is a preferable type of lung resection, even though the number of required incisions is usually higher compared to the video-assisted approac...
Lung Neoplasms Thoracic Surgery, Video-Assisted Pneumonectomy Aged Humans Neoplasm Recurrence, Local Robotics Lung Female Robotic Surgical Procedures
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Deep learning classifiers for computer-aided diagnosis of multiple lungs disease.

Journal of X-ray science and technology Jan 1, 2023
BACKGROUND: Computer aided diagnosis has gained momentum in the recent past. The advances in deep learning and availability of huge volumes of data along with increased computational capabilities has reshaped the diagnosis and prognosis procedures.
Diagnosis, Computer-Assisted Deep Learning COVID-19 Testing Lung Neoplasms Computers Lung Humans COVID-19
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Autosegmentation of lung computed tomography datasets using deep learning U-Net architecture.

Journal of cancer research and therapeutics Jan 1, 2023
AIM: Current radiotherapy treatment techniques require a large amount of imaging data for treatment planning which demand significant clinician's time to segment target volume and organs at risk (OARs). In this study, we propose to use U-net-based ar...
Deep Learning Lung Neoplasms Heart Tomography, X-Ray Computed Lung Humans
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[Introduction of Robot-assisted Lung Segmentectomy].

Kyobu geka. The Japanese journal of thoracic surgery Jan 1, 2023
Robot-assisted lung segmentectomy will be covered by insurance starting 2020. The results of the Japan Clinical Oncology Group( JCOG) 0802 trial have been reported, and the use of robot-assisted lung segmentectomy is expected to increase in the futur...
Lung Neoplasms Robotics Robotic Surgical Procedures Humans Lung Pneumonectomy
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Deep Learning-based Outcome Prediction in Progressive Fibrotic Lung Disease Using High-Resolution Computed Tomography.

American journal of respiratory and critical care medicine Oct 1, 2022
Reliable outcome prediction in patients with fibrotic lung disease using baseline high-resolution computed tomography (HRCT) data remains challenging. To evaluate the prognostic accuracy of a deep learning algorithm (SOFIA [Systematic Objective Fib...
Tomography, X-Ray Computed Lung Prospective Studies Idiopathic Pulmonary Fibrosis Prognosis Humans Lung Diseases, Interstitial Deep Learning Retrospective Studies
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[Lung parenchyma segmentation based on double scale parallel attention network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Aug 25, 2022
[]Automatic and accurate segmentation of lung parenchyma is essential for assisted diagnosis of lung cancer. In recent years, researchers in the field of deep learning have proposed a number of improved lung parenchyma segmentation methods based on U...
Neural Networks, Computer Tomography, X-Ray Computed Lung Algorithms Image Processing, Computer-Assisted
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Transfer Learning for Automated COVID-19 B-Line Classification in Lung Ultrasound.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2022
Lung ultrasound (LUS) as a diagnostic tool is gaining support for its role in the diagnosis and management of COVID-19 and a number of other lung pathologies. B-lines are a predominant feature in COVID-19, however LUS requires a skilled clinician to ...
Thorax Humans Deep Learning Ultrasonography COVID-19 Lung
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CellDART: cell type inference by domain adaptation of single-cell and spatial transcriptomic data.

Nucleic acids research Jun 10, 2022
Deciphering the cellular composition in genome-wide spatially resolved transcriptomic data is a critical task to clarify the spatial context of cells in a tissue. In this study, we developed a method, CellDART, which estimates the spatial distributio...
Neural Networks, Computer Brain Animals Humans Single-Cell Analysis Mice Lung Transcriptome
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