AIMC Topic: Lung Neoplasms

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Two different methods of bronchial dissection and coverage in robotic bilobectomy for advanced lung cancer.

Asian journal of endoscopic surgery Jul 3, 2022
INTRODUCTION: Due to its many technical advantages, the scope of robot-assisted thoracic surgery (RATS) is expanding to include extended pulmonary resection. Among such procedures, right bilobectomy is one with a high risk of inducing development of ...
Bronchi Bronchial Fistula Robotic Surgical Procedures Pneumonectomy Humans Carcinoma, Non-Small-Cell Lung Robotics Lung Neoplasms
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SANet: A Slice-Aware Network for Pulmonary Nodule Detection.

IEEE transactions on pattern analysis and machine intelligence Jul 1, 2022
Lung cancer is the most common cause of cancer death worldwide. A timely diagnosis of the pulmonary nodules makes it possible to detect lung cancer in the early stage, and thoracic computed tomography (CT) provides a convenient way to diagnose nodule...
Algorithms Tomography, X-Ray Computed Lung Neoplasms Humans Neural Networks, Computer
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Artificial intelligence in clinical applications for lung cancer: diagnosis, treatment and prognosis.

Clinical chemistry and laboratory medicine Jun 30, 2022
Artificial intelligence (AI) is a branch of computer science that includes research in robotics, language recognition, image recognition, natural language processing, and expert systems. AI is poised to change medical practice, and oncology is not an...
Artificial Intelligence Machine Learning Prognosis Lung Neoplasms Forecasting Humans
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Use of deep learning to predict postoperative recurrence of lung adenocarcinoma from preoperative CT.

International journal of computer assisted radiology and surgery Jun 28, 2022
PURPOSE: Although surgery is the primary treatment for lung cancer, some patients experience recurrence at a certain rate. If postoperative recurrence can be predicted early before treatment is initiated, it may be possible to provide individualized ...
Lung Neoplasms Adenocarcinoma of Lung Tomography, X-Ray Computed Deep Learning Humans Retrospective Studies
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Radiologists with and without deep learning-based computer-aided diagnosis: comparison of performance and interobserver agreement for characterizing and diagnosing pulmonary nodules/masses.

European radiology Jun 25, 2022
OBJECTIVES: To compare the performance of radiologists in characterizing and diagnosing pulmonary nodules/masses with and without deep learning (DL)-based computer-aided diagnosis (CAD).
Deep Learning Lung Neoplasms Sensitivity and Specificity Diagnosis, Computer-Assisted Radiologists Observer Variation Multiple Pulmonary Nodules Solitary Pulmonary Nodule Computers Reproducibility of Results Humans
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Deep Learning and Structure-Based Virtual Screening for Drug Discovery against NEK7: A Novel Target for the Treatment of Cancer.

Molecules (Basel, Switzerland) Jun 25, 2022
NIMA-related kinase7 (NEK7) plays a multifunctional role in cell division and NLRP3 inflammasone activation. A typical expression or any mutation in the genetic makeup of NEK7 leads to the development of cancer malignancies and fatal inflammatory dis...
Molecular Dynamics Simulation NIMA-Related Kinases Humans Carcinoma, Non-Small-Cell Lung Molecular Docking Simulation Deep Learning Early Detection of Cancer Drug Discovery Lung Neoplasms
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Accuracy of two deep learning-based reconstruction methods compared with an adaptive statistical iterative reconstruction method for solid and ground-glass nodule volumetry on low-dose and ultra-low-dose chest computed tomography: A phantom study.

PloS one Jun 23, 2022
No published studies have evaluated the accuracy of volumetric measurement of solid nodules and ground-glass nodules on low-dose or ultra-low-dose chest computed tomography, reconstructed using deep learning-based algorithms. This is an important iss...
Early Detection of Cancer Radiographic Image Interpretation, Computer-Assisted Deep Learning Algorithms Lung Neoplasms Radiation Dosage Tomography, X-Ray Computed Humans Phantoms, Imaging
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A deep learning based CT image analytics protocol to identify lung adenocarcinoma category and high-risk tumor area.

STAR protocols Jun 22, 2022
We present a protocol which implements deep learning-based identification of the lung adenocarcinoma category with high accuracy and generalizability, and labeling of the high-risk area on Computed Tomography (CT) images. The protocol details the exe...
Tomography, X-Ray Computed Deep Learning Humans Adenocarcinoma of Lung Image Processing, Computer-Assisted Lung Neoplasms
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Discriminating TB lung nodules from early lung cancers using deep learning.

BMC medical informatics and decision making Jun 21, 2022
BACKGROUND: In developing countries where both high rates of smoking and endemic tuberculosis (TB) are often present, identification of early lung cancer can be significantly confounded by the presence of nodules such as those due to latent TB (LTB)....
Humans Tuberculosis Deep Learning Neural Networks, Computer Lung Neoplasms Lung
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VCNet: Hybrid Deep Learning Model for Detection and Classification of Lung Carcinoma Using Chest Radiographs.

Frontiers in public health Jun 20, 2022
Detection of malignant lung nodules from Computed Tomography (CT) images is a significant task for radiologists. But, it is time-consuming in nature. Despite numerous breakthroughs in studies on the application of deep learning models for the identif...
Lung Neoplasms Lung Humans Carcinoma Deep Learning Tomography, X-Ray Computed
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