AIMC Topic: Lung Neoplasms
Clear Filters Showing 1531 to 1540 of 1658 articles
Unsupervised Detection of Lung Nodules in Chest Radiography Using Generative Adversarial Networks.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
Lung nodules are commonly missed in chest radiographs. We propose and evaluate P-AnoGAN, an unsupervised anomaly detection approach for lung nodules in radiographs. P-AnoGAN modifies the fast anomaly detection generative adversarial network (f-AnoGAN...
Dual Skip Connections Minimize the False Positive Rate of Lung Nodule Detection in CT images.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
Pulmonary cancer is one of the most commonly diagnosed and fatal cancers and is often diagnosed by incidental findings on computed tomography. Automated pulmonary nodule detection is an essential part of computer-aided diagnosis, which is still facin...
Multi-Scale Aggregated-Dilation Network for ex-vivo Lung Cancer Detection with Fluorescence Lifetime Imaging Endomicroscopy.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
Multi-scale architectures at a granular level are characterised by separating input features into groups and applying multi-scale feature extractions to the split input features, and thus the correlations among the input features as global informatio...
Attention Based Deep Multiple Instance Learning Approach for Lung Cancer Prediction using Histopathological Images.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
Deep Neural Networks using histopathological images as an input currently embody one of the gold standards in automated lung cancer diagnostic solutions, with Deep Convolutional Neural Networks achieving the state of the art values for tissue type cl...
Accurate segmentation for different types of lung nodules on CT images using improved U-Net convolutional network.
Medicine
Oct 8, 2021
Since lung nodules on computed tomography images can have different shapes, contours, textures or locations and may be attached to neighboring blood vessels or pleural surfaces, accurate segmentation is still challenging. In this study, we propose an...
End-to-End Non-Small-Cell Lung Cancer Prognostication Using Deep Learning Applied to Pretreatment Computed Tomography.
JCO clinical cancer informatics
Oct 1, 2021
PURPOSE: Clinical TNM staging is a key prognostic factor for patients with lung cancer and is used to inform treatment and monitoring. Computed tomography (CT) plays a central role in defining the stage of disease. Deep learning applied to pretreatme...
NMCMDA: neural multicategory MiRNA-disease association prediction.
Briefings in bioinformatics
Sep 2, 2021
MOTIVATION: There is growing evidence showing that the dysregulations of miRNAs cause diseases through various kinds of the underlying mechanism. Thus, predicting the multiple-category associations between microRNAs (miRNAs) and diseases plays an imp...
GAERF: predicting lncRNA-disease associations by graph auto-encoder and random forest.
Briefings in bioinformatics
Sep 2, 2021
Predicting disease-related long non-coding RNAs (lncRNAs) is beneficial to finding of new biomarkers for prevention, diagnosis and treatment of complex human diseases. In this paper, we proposed a machine learning techniques-based classification appr...
Comparison between robot-assisted thoracoscopic surgery and video-assisted thoracoscopic surgery for mediastinal and hilar lymph node dissection in lung cancer surgery.
Interactive cardiovascular and thoracic surgery
Aug 18, 2021
OBJECTIVES: Lymph node dissection (LND) with robot-assisted thoracoscopic surgery (RATS) in lung cancer surgery has not been fully evaluated. The aim of this study was to compare LND surgical results between video-assisted thoracoscopic surgery (VATS...
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