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Carcinoma, Non-Small-Cell Lung

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Machine Learning for Early Lung Cancer Identification Using Routine Clinical and Laboratory Data.

American journal of respiratory and critical care medicine Aug 15, 2021
Most lung cancers are diagnosed at an advanced stage. Presymptomatic identification of high-risk individuals can prompt earlier intervention and improve long-term outcomes. To develop a model to predict a future diagnosis of lung cancer on the basi...
Retrospective Studies Female Aged Aged, 80 and over Sensitivity and Specificity Humans Machine Learning Lung Neoplasms Carcinoma, Non-Small-Cell Lung Early Detection of Cancer Odds Ratio Clinical Decision Rules Male Middle Aged Case-Control Studies ROC Curve
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Differentiating Small-Cell Lung Cancer From Non-Small-Cell Lung Cancer Brain Metastases Based on MRI Using Efficientnet and Transfer Learning Approach.

Technology in cancer research & treatment Jan 1, 2021
Differentiation between small-cell lung cancer (SCLC) from non-small-cell lung cancer (NSCLC) brain metastases is crucial due to the different clinical behaviors of the two tumor types. We propose the use of a deep learning and transfer learning appr...
Image Interpretation, Computer-Assisted Small Cell Lung Carcinoma Machine Learning Prognosis Brain Neoplasms Follow-Up Studies Retrospective Studies Male Magnetic Resonance Imaging Female Middle Aged Humans Diagnosis, Differential ROC Curve Lung Neoplasms Carcinoma, Non-Small-Cell Lung
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Comparison between atlas and convolutional neural network based automatic segmentation of multiple organs at risk in non-small cell lung cancer.

Medicine Aug 21, 2020
Delineation of organs at risk (OARs) is important but time consuming for radiotherapy planning. Automatic segmentation of OARs based on convolutional neural network (CNN) has been established for lung cancer patients at our institution. The aim of th...
Organs at Risk Radiotherapy Planning, Computer-Assisted Spinal Cord Retrospective Studies Reproducibility of Results Lung Time Factors Liver Esophagus Heart Lung Neoplasms Carcinoma, Non-Small-Cell Lung Humans Neural Networks, Computer
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Next-Generation Radiogenomics Sequencing for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients Using Multimodal Imaging and Machine Learning Algorithms.

Molecular imaging and biology Aug 1, 2020
PURPOSE: Considerable progress has been made in the assessment and management of non-small cell lung cancer (NSCLC) patients based on mutation status in the epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral oncogene (KRAS). At the...
Machine Learning Algorithms Female Aged Humans Multimodal Imaging Area Under Curve Mutation Positron-Emission Tomography High-Throughput Nucleotide Sequencing Male Lung Neoplasms Genomics Carcinoma, Non-Small-Cell Lung Multivariate Analysis ErbB Receptors Proto-Oncogene Proteins p21(ras)
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Classifying non-small cell lung cancer types and transcriptomic subtypes using convolutional neural networks.

Journal of the American Medical Informatics Association : JAMIA May 1, 2020
OBJECTIVE: Non-small cell lung cancer is a leading cause of cancer death worldwide, and histopathological evaluation plays the primary role in its diagnosis. However, the morphological patterns associated with the molecular subtypes have not been sys...
Neural Networks, Computer Machine Learning Carcinoma, Squamous Cell Humans Adenocarcinoma of Lung Transcriptome ROC Curve Lung Neoplasms Carcinoma, Non-Small-Cell Lung
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The Relative Importance of Clinical and Socio-demographic Variables in Prognostic Prediction in Non-Small Cell Lung Cancer: A Variable Importance Approach.

Medical care May 1, 2020
BACKGROUND: Prognostic modeling in health care has been predominantly statistical, despite a rapid growth of literature on machine-learning approaches in biological data analysis. We aim to assess the relative importance of variables in predicting ov...
Random Allocation Whole Body Imaging Female Positron Emission Tomography Computed Tomography Aged Neoplasm Staging Adult Humans Radiopharmaceuticals Lung Neoplasms Male Machine Learning Tumor Burden Middle Aged Carcinoma, Non-Small-Cell Lung Prognosis Comorbidity Models, Statistical Retrospective Studies
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[Prediction of gene mutation in lung cancer based on deep learning and histomorphology analysis].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Feb 25, 2020
Lung cancer is a most common malignant tumor of the lung and is the cancer with the highest morbidity and mortality worldwide. For patients with advanced non-small cell lung cancer who have undergone epidermal growth factor receptor (EGFR) gene mutat...
Deep Learning Lung Neoplasms Carcinoma, Non-Small-Cell Lung Mutation ErbB Receptors Humans
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Discussion.

The Journal of thoracic and cardiovascular surgery Nov 1, 2019
Robotics Robotic Surgical Procedures Propensity Score Humans Lung Neoplasms Carcinoma, Non-Small-Cell Lung
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DL-CNV: A deep learning method for identifying copy number variations based on next generation target sequencing.

Mathematical biosciences and engineering : MBE Sep 30, 2019
Copy number variations (CNVs) play an important role in many types of cancer. With the rapid development of next generation sequencing (NGS) techniques, many methods for detecting CNVs of a single sample have emerged: (i) require genome-wide data of ...
Exons Lung Neoplasms Sensitivity and Specificity Proto-Oncogene Proteins c-met Humans Carcinoma, Non-Small-Cell Lung Deep Learning High-Throughput Nucleotide Sequencing Algorithms Genome-Wide Association Study In Situ Hybridization, Fluorescence ROC Curve Databases, Factual Reproducibility of Results DNA Copy Number Variations Area Under Curve Receptor, ErbB-2 Genome, Human False Positive Reactions
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Machine-Learning and Stochastic Tumor Growth Models for Predicting Outcomes in Patients With Advanced Non-Small-Cell Lung Cancer.

JCO clinical cancer informatics Sep 1, 2019
PURPOSE: The prediction of clinical outcomes for patients with cancer is central to precision medicine and the design of clinical trials. We developed and validated machine-learning models for three important clinical end points in patients with adva...
Stochastic Processes Algorithms Prognosis Lung Neoplasms Treatment Outcome Carcinoma, Non-Small-Cell Lung Combined Modality Therapy Neoplasm Metastasis Humans Tumor Burden Randomized Controlled Trials as Topic Molecular Targeted Therapy Machine Learning Neoplasm Staging Kaplan-Meier Estimate Models, Biological
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