AIMC Topic: Lung Neoplasms

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Deep-chest: Multi-classification deep learning model for diagnosing COVID-19, pneumonia, and lung cancer chest diseases.

Computers in biology and medicine Mar 19, 2021
Corona Virus Disease (COVID-19) has been announced as a pandemic and is spreading rapidly throughout the world. Early detection of COVID-19 may protect many infected people. Unfortunately, COVID-19 can be mistakenly diagnosed as pneumonia or lung can...
Early Detection of Cancer SARS-CoV-2 Pneumonia Deep Learning Lung Neoplasms Humans COVID-19 Algorithms
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Deep Learning to Estimate Biological Age From Chest Radiographs.

JACC. Cardiovascular imaging Mar 17, 2021
OBJECTIVES: The goal of this study was to assess whether a deep learning estimate of age from a chest radiograph image (CXR-Age) can predict longevity beyond chronological age.
Predictive Value of Tests Male Aging Deep Learning Child, Preschool Humans Lung Neoplasms Young Adult Early Detection of Cancer Adult
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Expanding TNM for lung cancer through machine learning.

Thoracic cancer Mar 13, 2021
BACKGROUND: Expanding the tumor, lymph node, metastasis (TNM) staging system by accommodating new prognostic and predictive factors for cancer will improve patient stratification and survival prediction. Here, we introduce machine learning for incorp...
Neoplasm Staging Male Middle Aged Lung Neoplasms Humans Machine Learning Female Adult
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Development and validation of a clinically applicable deep learning strategy (HONORS) for pulmonary nodule classification at CT: A retrospective multicentre study.

Lung cancer (Amsterdam, Netherlands) Mar 11, 2021
PURPOSE: To propose a practical strategy for the clinical application of deep learning algorithm, i.e., Hierarchical-Ordered Network-ORiented Strategy (HONORS), and a new approach to pulmonary nodule classification in various clinical scenarios, i.e....
Humans Retrospective Studies Lung Neoplasms Tomography, X-Ray Computed Deep Learning Multiple Pulmonary Nodules Solitary Pulmonary Nodule
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Deep learning classification of lung cancer histology using CT images.

Scientific reports Mar 9, 2021
Tumor histology is an important predictor of therapeutic response and outcomes in lung cancer. Tissue sampling for pathologist review is the most reliable method for histology classification, however, recent advances in deep learning for medical imag...
Lung Neoplasms Carcinoma, Non-Small-Cell Lung Tomography, X-Ray Computed Lung Deep Learning Humans Neural Networks, Computer
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Towards radiologist-level cancer risk assessment in CT lung screening using deep learning.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Mar 5, 2021
PURPOSE: Lung cancer is the leading cause of cancer mortality in the US, responsible for more deaths than breast, prostate, colon and pancreas cancer combined and large population studies have indicated that low-dose computed tomography (CT) screenin...
Deep Learning Male Humans Lung Neoplasms Radiologists Tomography, X-Ray Computed Risk Assessment Early Detection of Cancer Lung
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Automated detection of lung nodules and coronary artery calcium using artificial intelligence on low-dose CT scans for lung cancer screening: accuracy and prognostic value.

BMC medicine Mar 4, 2021
BACKGROUND: Artificial intelligence (AI) in diagnostic radiology is undergoing rapid development. Its potential utility to improve diagnostic performance for cardiopulmonary events is widely recognized, but the accuracy and precision have yet to be d...
Humans Artificial Intelligence Female Male Cohort Studies Prognosis Retrospective Studies Tomography, X-Ray Computed Coronary Vessels Lung Neoplasms Early Detection of Cancer Calcium
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Computer-aided diagnosis of ground glass pulmonary nodule by fusing deep learning and radiomics features.

Physics in medicine and biology Mar 4, 2021
OBJECTIVES: This study aims to develop a computer-aided diagnosis (CADx) scheme to classify between benign and malignant ground glass nodules (GGNs), and fuse deep leaning and radiomics imaging features to improve the classification performance.
Humans Tomography, X-Ray Computed Lung Neoplasms Support Vector Machine Adenocarcinoma of Lung Diagnosis, Computer-Assisted Deep Learning Image Processing, Computer-Assisted
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Data-efficient and weakly supervised computational pathology on whole-slide images.

Nature biomedical engineering Mar 1, 2021
Deep-learning methods for computational pathology require either manual annotation of gigapixel whole-slide images (WSIs) or large datasets of WSIs with slide-level labels and typically suffer from poor domain adaptation and interpretability. Here we...
Carcinoma, Renal Cell Image Interpretation, Computer-Assisted Kidney Neoplasms Histocytochemistry Lung Neoplasms Humans Smartphone Deep Learning Lymphatic Metastasis Carcinoma, Non-Small-Cell Lung Area Under Curve Microscopy
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Assessment of an Exhaled Breath Test Using High-Pressure Photon Ionization Time-of-Flight Mass Spectrometry to Detect Lung Cancer.

JAMA network open Mar 1, 2021
IMPORTANCE: Exhaled breath is an attractive option for cancer detection. A sensitive and reliable breath test has the potential to greatly facilitate diagnoses and therapeutic monitoring of lung cancer.
Male Humans Middle Aged Retrospective Studies Early Detection of Cancer Algorithms Support Vector Machine Lung Neoplasms Female Breath Tests Follow-Up Studies Reproducibility of Results Exhalation Mass Spectrometry
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