AIMC Topic: Lung Neoplasms

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Lung cancer prediction by Deep Learning to identify benign lung nodules.

Lung cancer (Amsterdam, Netherlands)
INTRODUCTION: Deep Learning has been proposed as promising tool to classify malignant nodules. Our aim was to retrospectively validate our Lung Cancer Prediction Convolutional Neural Network (LCP-CNN), which was trained on US screening data, on an in...

Wavelet decomposition facilitates training on small datasets for medical image classification by deep learning.

Histochemistry and cell biology
The adoption of low-dose computed tomography (LDCT) as the standard of care for lung cancer screening results in decreased mortality rates in high-risk population while increasing false-positive rate. Convolutional neural networks provide an ideal op...

A Machine Learning-Based Investigation of Gender-Specific Prognosis of Lung Cancers.

Medicina (Kaunas, Lithuania)
BACKGROUND AND OBJECTIVE: Primary lung cancer is a lethal and rapidly-developing cancer type and is one of the most leading causes of cancer deaths.

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Sensors (Basel, Switzerland)
The field of Medicine and Healthcare has attained revolutionary advancements in the last forty years. Within this period, the actual reasons behind numerous diseases were unveiled, novel diagnostic methods were designed, and new medicines were develo...

Classification of malignant lung cancer using deep learning.

Journal of medical engineering & technology
In the automatic detection of suspicious shaded regions on CT images derived from the LIDC-IDRI dataset, the diagnostic system plays a significant role. This paper introduces an automatic recognition method for lung nodules of the regions of concern ...

Robotic Pneumonectomy for Lung Cancer: Perioperative Outcomes and Factors Leading to Conversion to Thoracotomy.

Innovations (Philadelphia, Pa.)
OBJECTIVE: In the tide of robot-assisted minimally invasive surgery, few cases of robot-assisted pneumonectomy exist in the literature. This study evaluates the perioperative outcomes and risk factors for conversion to thoracotomy with an initial rob...

Synthetic CT image generation of shape-controlled lung cancer using semi-conditional InfoGAN and its applicability for type classification.

International journal of computer assisted radiology and surgery
PURPOSE: In recent years, convolutional neural network (CNN), an artificial intelligence technology with superior image recognition, has become increasingly popular and frequently used for classification tasks in medical imaging. However, the amount ...

3D multi-scale deep convolutional neural networks for pulmonary nodule detection.

PloS one
With the rapid development of big data and artificial intelligence technology, computer-aided pulmonary nodule detection based on deep learning has achieved some successes. However, the sizes of pulmonary nodules vary greatly, and the pulmonary nodul...

Lung cancer histology classification from CT images based on radiomics and deep learning models.

Medical & biological engineering & computing
Adenocarcinoma (AC) and squamous cell carcinoma (SCC) are frequent reported cases of non-small cell lung cancer (NSCLC), responsible for a large fraction of cancer deaths worldwide. In this study, we aim to investigate the potential of NSCLC histolog...