AIMC Topic: Lung Neoplasms
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A Staging Auxiliary Diagnosis Model for Nonsmall Cell Lung Cancer Based on the Intelligent Medical System.
Computational and mathematical methods in medicine
Feb 8, 2021
At present, human health is threatened by many diseases, and lung cancer is one of the most dangerous tumors that threaten human life. In most developing countries, due to the large population and lack of medical resources, it is difficult for doctor...
Lung Cancer and Granuloma Identification Using a Deep Learning Model to Extract 3-Dimensional Radiomics Features in CT Imaging.
Clinical lung cancer
Feb 6, 2021
BACKGROUND: We aimed to evaluate a deep learning (DL) model combining perinodular and intranodular radiomics features and clinical features for preoperative differentiation of solitary granuloma nodules (GNs) from solid lung cancer nodules in patient...
Deep Learning Methods for Lung Cancer Segmentation in Whole-Slide Histopathology Images-The ACDC@LungHP Challenge 2019.
IEEE journal of biomedical and health informatics
Feb 5, 2021
Accurate segmentation of lung cancer in pathology slides is a critical step in improving patient care. We proposed the ACDC@LungHP (Automatic Cancer Detection and Classification in Whole-slide Lung Histopathology) challenge for evaluating different c...
Use of a Commercially Available Deep Learning Algorithm to Measure the Solid Portions of Lung Cancer Manifesting as Subsolid Lesions at CT: Comparisons with Radiologists and Invasive Component Size at Pathologic Examination.
Radiology
Feb 2, 2021
Background The solid portion size of lung cancer lesions manifesting as subsolid lesions is key in their management, but the automatic measurement of such lesions by means of a deep learning (DL) algorithm needs evaluation. Purpose To evaluate the pe...
Integrating Multiomics Information in Deep Learning Architectures for Joint Actuarial Outcome Prediction in Non-Small Cell Lung Cancer Patients After Radiation Therapy.
International journal of radiation oncology, biology, physics
Feb 1, 2021
PURPOSE: Novel actuarial deep learning neural network (ADNN) architectures are proposed for joint prediction of radiation therapy outcomes-radiation pneumonitis (RP) and local control (LC)-in stage III non-small cell lung cancer (NSCLC) patients. Unl...
Lung cancer prediction by Deep Learning to identify benign lung nodules.
Lung cancer (Amsterdam, Netherlands)
Jan 31, 2021
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
Jan 27, 2021
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)
Jan 22, 2021
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)
Jan 22, 2021
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
Jan 15, 2021
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 ...
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