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LAURENCE EDWARD COURT to Carcinoma, Non-Small-Cell Lung

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This is a "connection" page, showing publications LAURENCE EDWARD COURT has written about Carcinoma, Non-Small-Cell Lung.
LAURENCE EDWARD COURT
Connection Strength
2.677
Carcinoma, Non-Small-Cell Lung
  1. Effects of alterations in positron emission tomography imaging parameters on radiomics features. PLoS One. 2019; 14(9):e0221877.
    View in: PubMed
    Score: 0.205
  2. Matching and Homogenizing Convolution Kernels for Quantitative Studies in Computed Tomography. Invest Radiol. 2019 05; 54(5):288-295.
    View in: PubMed
    Score: 0.200
  3. Differences in Normal Tissue Response in the Esophagus Between Proton and Photon Radiation Therapy for Non-Small Cell Lung Cancer Using In?Vivo Imaging Biomarkers. Int J Radiat Oncol Biol Phys. 2017 11 15; 99(4):1013-1020.
    View in: PubMed
    Score: 0.177
  4. Delta-radiomics features for the prediction of patient outcomes in non-small cell lung cancer. Sci Rep. 2017 04 03; 7(1):588.
    View in: PubMed
    Score: 0.174
  5. Can radiomics features be reproducibly measured from CBCT images for patients with non-small cell lung cancer? Med Phys. 2015 Dec; 42(12):6784-97.
    View in: PubMed
    Score: 0.158
  6. NSCLC tumor shrinkage prediction using quantitative image features. Comput Med Imaging Graph. 2016 Apr; 49:29-36.
    View in: PubMed
    Score: 0.158
  7. Potential Use of (18)F-fluorodeoxyglucose Positron Emission Tomography-Based Quantitative Imaging Features for Guiding Dose Escalation in Stage III Non-Small Cell Lung Cancer. Int J Radiat Oncol Biol Phys. 2016 Feb 01; 94(2):368-76.
    View in: PubMed
    Score: 0.157
  8. Stage III Non-Small Cell Lung Cancer: Prognostic Value of FDG PET Quantitative Imaging Features Combined with Clinical Prognostic Factors. Radiology. 2016 Jan; 278(1):214-22.
    View in: PubMed
    Score: 0.154
  9. Preliminary investigation into sources of uncertainty in quantitative imaging features. Comput Med Imaging Graph. 2015 Sep; 44:54-61.
    View in: PubMed
    Score: 0.152
  10. Prognostic value and reproducibility of pretreatment CT texture features in stage III non-small cell lung cancer. Int J Radiat Oncol Biol Phys. 2014 Nov 15; 90(4):834-42.
    View in: PubMed
    Score: 0.145
  11. High quality machine-robust image features: identification in nonsmall cell lung cancer computed tomography images. Med Phys. 2013 Dec; 40(12):121916.
    View in: PubMed
    Score: 0.138
  12. Deep learning-based automatic segmentation of cardiac substructures for lung cancers. Radiother Oncol. 2024 Feb; 191:110061.
    View in: PubMed
    Score: 0.069
  13. Quantifying the Effect of 4-Dimensional Computed Tomography-Based Deformable Dose Accumulation on Representing Radiation Damage for Patients with Locally Advanced Non-Small Cell Lung Cancer Treated with Standard-Fractionated Intensity-Modulated Radiation Therapy. Int J Radiat Oncol Biol Phys. 2024 Jan 01; 118(1):231-241.
    View in: PubMed
    Score: 0.067
  14. Accelerated Hypofractionated Image-Guided vs Conventional Radiotherapy for Patients With Stage II/III Non-Small Cell Lung Cancer and Poor Performance Status: A Randomized Clinical Trial. JAMA Oncol. 2021 Oct 01; 7(10):1497-1505.
    View in: PubMed
    Score: 0.059
  15. Development and application of an elastic net logistic regression model to investigate the impact of cardiac substructure dose on radiation-induced pericardial effusion in patients with NSCLC. Acta Oncol. 2020 Oct; 59(10):1193-1200.
    View in: PubMed
    Score: 0.055
  16. Lung tumor segmentation methods: Impact on the uncertainty of radiomics features for non-small cell lung cancer. PLoS One. 2018; 13(10):e0205003.
    View in: PubMed
    Score: 0.048
  17. Comprehensive Investigation on Controlling for CT Imaging Variabilities in Radiomics Studies. Sci Rep. 2018 08 29; 8(1):13047.
    View in: PubMed
    Score: 0.048
  18. Effect of tube current on computed tomography radiomic features. Sci Rep. 2018 02 05; 8(1):2354.
    View in: PubMed
    Score: 0.046
  19. Development of an Immune-Pathology Informed Radiomics Model for Non-Small Cell Lung Cancer. Sci Rep. 2018 01 31; 8(1):1922.
    View in: PubMed
    Score: 0.046
  20. Prognostic value of combining a quantitative image feature from positron emission tomography with clinical factors in oligometastatic non-small cell lung cancer. Radiother Oncol. 2018 02; 126(2):362-367.
    View in: PubMed
    Score: 0.045
  21. Development and Validation of a Predictive Radiomics Model for Clinical Outcomes in Stage I Non-small Cell Lung Cancer. Int J Radiat Oncol Biol Phys. 2018 11 15; 102(4):1090-1097.
    View in: PubMed
    Score: 0.045
  22. A Novel Methodology using CT Imaging Biomarkers to Quantify Radiation Sensitivity in the Esophagus with Application to Clinical Trials. Sci Rep. 2017 07 20; 7(1):6034.
    View in: PubMed
    Score: 0.044
  23. (18)F-Fluorodeoxyglucose Positron Emission Tomography Can Quantify and Predict Esophageal Injury During Radiation Therapy. Int J Radiat Oncol Biol Phys. 2016 11 01; 96(3):670-8.
    View in: PubMed
    Score: 0.041
  24. Perturbation of water-equivalent thickness as a surrogate for respiratory motion in proton therapy. J Appl Clin Med Phys. 2016 03 08; 17(2):368-378.
    View in: PubMed
    Score: 0.040
  25. Measuring Computed Tomography Scanner Variability of Radiomics Features. Invest Radiol. 2015 Nov; 50(11):757-65.
    View in: PubMed
    Score: 0.039
  26. Objectively Quantifying Radiation Esophagitis With Novel Computed Tomography-Based Metrics. Int J Radiat Oncol Biol Phys. 2016 Feb 01; 94(2):385-93.
    View in: PubMed
    Score: 0.039
  27. Effects of respiratory motion on passively scattered proton therapy versus intensity modulated photon therapy for stage III lung cancer: are proton plans more sensitive to breathing motion? Int J Radiat Oncol Biol Phys. 2013 Nov 01; 87(3):576-82.
    View in: PubMed
    Score: 0.034
  28. Analysis of esophageal-sparing treatment plans for patients with high-grade esophagitis. J Appl Clin Med Phys. 2013 Jul 08; 14(4):4248.
    View in: PubMed
    Score: 0.033
  29. Statistical assessment of proton treatment plans under setup and range uncertainties. Int J Radiat Oncol Biol Phys. 2013 Aug 01; 86(5):1007-13.
    View in: PubMed
    Score: 0.033
  30. Automatic segmentation of cardiac substructures from noncontrast CT images: accurate enough for dosimetric analysis? Acta Oncol. 2019 Jan; 58(1):81-87.
    View in: PubMed
    Score: 0.012
  31. The utility of quantitative CT radiomics features for improved prediction of radiation pneumonitis. Med Phys. 2018 Nov; 45(11):5317-5324.
    View in: PubMed
    Score: 0.012
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.