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Carcinoma, Non-Small-Cell Lung

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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...
Humans Cytokines Female Aged Treatment Outcome Carcinoma, Non-Small-Cell Lung MicroRNAs Positron-Emission Tomography Radiation Pneumonitis Male Middle Aged Deep Learning Lung Neoplasms
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Repeatability and reproducibility study of radiomic features on a phantom and human cohort.

Scientific reports Jan 21, 2021
The repeatability and reproducibility of radiomic features extracted from CT scans need to be investigated to evaluate the temporal stability of imaging features with respect to a controlled scenario (test-retest), as well as their dependence on acqu...
Adult Male Middle Aged Cohort Studies Magnetic Resonance Imaging Phantoms, Imaging Image Processing, Computer-Assisted Carcinoma, Non-Small-Cell Lung Humans Machine Learning Computer Simulation Tomography, X-Ray Computed Female Reproducibility of Results Aged Aged, 80 and over
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Lung cancer histology classification from CT images based on radiomics and deep learning models.

Medical & biological engineering & computing Jan 7, 2021
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...
Carcinoma, Non-Small-Cell Lung Humans Neural Networks, Computer Tomography, X-Ray Computed Deep Learning Lung Neoplasms
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Assessing PD-L1 expression in non-small cell lung cancer and predicting responses to immune checkpoint inhibitors using deep learning on computed tomography images.

Theranostics Jan 1, 2021
This study aimed to use computed tomography (CT) images to assess PD-L1 expression in non-small cell lung cancer (NSCLC) and predict response to immunotherapy. We retrospectively analyzed a PD-L1 expression dataset that consisted of 939 consecutive...
Humans Retrospective Studies Tomography, X-Ray Computed Female Immune Checkpoint Inhibitors Lung Neoplasms B7-H1 Antigen Immunotherapy Carcinoma, Non-Small-Cell Lung Aged Male Middle Aged Deep Learning
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Network-based drug sensitivity prediction.

BMC medical genomics Dec 28, 2020
BACKGROUND: Drug sensitivity prediction and drug responsive biomarker selection on high-throughput genomic data is a critical step in drug discovery. Many computational methods have been developed to serve this purpose including several deep neural n...
Carcinoma, Non-Small-Cell Lung Gene Regulatory Networks Lung Neoplasms Computational Biology Humans Gene Expression Regulation, Neoplastic Neural Networks, Computer Software Antineoplastic Agents Gene Expression Profiling Deep Learning Prognosis Biomarkers, Tumor
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Development and Validation of a Machine Learning Model to Explore Tyrosine Kinase Inhibitor Response in Patients With Stage IV EGFR Variant-Positive Non-Small Cell Lung Cancer.

JAMA network open Dec 1, 2020
IMPORTANCE: An end-to-end efficacy evaluation approach for identifying progression risk after epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitor (TKI) therapy in patients with stage IV EGFR variant-positive non-small cell lung cancer (...
Antineoplastic Protocols Survival Analysis Proportional Hazards Models ErbB Receptors Protein Kinase Inhibitors Female Male Middle Aged Antineoplastic Agents Predictive Value of Tests Neoplasm Staging Mutation Lung Neoplasms Carcinoma, Non-Small-Cell Lung Humans Machine Learning Prognosis
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Using Auto-Segmentation to Reduce Contouring and Dose Inconsistency in Clinical Trials: The Simulated Impact on RTOG 0617.

International journal of radiation oncology, biology, physics Nov 13, 2020
PURPOSE: Contouring inconsistencies are known but understudied in clinical radiation therapy trials. We applied auto-contouring to the Radiation Therapy Oncology Group (RTOG) 0617 dose escalation trial data. We hypothesized that the trial heart doses...
Middle Aged Deep Learning Lung Neoplasms Carcinoma, Non-Small-Cell Lung Aged Aged, 80 and over Adult Male Proportional Hazards Models Radiotherapy Dosage Clinical Trials, Phase III as Topic Statistics, Nonparametric Heart Algorithms Organs at Risk Tomography, X-Ray Computed Confidence Intervals Female Humans Linear Models
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Quantitative Structure-Mutation-Activity Relationship Tests (QSMART) model for protein kinase inhibitor response prediction.

BMC bioinformatics Nov 12, 2020
BACKGROUND: Protein kinases are a large family of druggable proteins that are genomically and proteomically altered in many human cancers. Kinase-targeted drugs are emerging as promising avenues for personalized medicine because of the differential r...
Quantitative Structure-Activity Relationship ErbB Receptors Humans Protein Kinase Inhibitors Lapatinib Afatinib Lung Neoplasms Neural Networks, Computer Carcinoma, Non-Small-Cell Lung Precision Medicine Mutation Cell Line, Tumor MAP Kinase Signaling System Protein Interaction Maps
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Radiomic Detection of EGFR Mutations in NSCLC.

Cancer research Nov 4, 2020
Radiomics is defined as the use of automated or semi-automated post-processing and analysis of multiple features derived from imaging exams. Extracted features might generate models able to predict the molecular profile of solid tumors. The aim of th...
Machine Learning Algorithms Tomography, X-Ray Computed Humans Lung Neoplasms Female Carcinoma, Non-Small-Cell Lung Adenocarcinoma Reproducibility of Results Area Under Curve ErbB Receptors Male Mutation ROC Curve
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Predicting Deep Learning Based Multi-Omics Parallel Integration Survival Subtypes in Lung Cancer Using Reverse Phase Protein Array Data.

Biomolecules Oct 19, 2020
Mortality attributed to lung cancer accounts for a large fraction of cancer deaths worldwide. With increasing mortality figures, the accurate prediction of prognosis has become essential. In recent years, multi-omics analysis has emerged as a useful ...
Models, Theoretical Male Protein Array Analysis Deep Learning Humans Carcinoma, Non-Small-Cell Lung Genomics Machine Learning DNA Methylation Proteomics Prognosis Disease-Free Survival Female
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