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Raymond H Mak, M.D.

Co-Author

This page shows the publications co-authored by Raymond Mak and Hugo Aerts.
Connection Strength

7.334
  1. Mean Heart Dose Is an Inadequate Surrogate for Left Anterior Descending Coronary Artery Dose and the Risk of Major Adverse Cardiac Events in Lung Cancer Radiation Therapy. Int J Radiat Oncol Biol Phys. 2021 08 01; 110(5):1473-1479.
    View in: PubMed
    Score: 0.237
  2. Deep learning classification of lung cancer histology using CT images. Sci Rep. 2021 Mar 09; 11(1):5471.
    View in: PubMed
    Score: 0.237
  3. Deep-learning system to improve the quality and efficiency of volumetric heart segmentation for breast cancer. NPJ Digit Med. 2021 Mar 05; 4(1):43.
    View in: PubMed
    Score: 0.237
  4. Association of Left Anterior Descending Coronary Artery Radiation Dose With Major Adverse Cardiac Events and Mortality in Patients With Non-Small Cell Lung Cancer. JAMA Oncol. 2021 Feb 01; 7(2):206-219.
    View in: PubMed
    Score: 0.236
  5. Statin Use, Heart Radiation Dose, and Survival in Locally Advanced Lung Cancer. Pract Radiat Oncol. 2021 Sep-Oct; 11(5):e459-e467.
    View in: PubMed
    Score: 0.235
  6. Approaching autonomy in medical artificial intelligence. Lancet Digit Health. 2020 09; 2(9):e447-e449.
    View in: PubMed
    Score: 0.229
  7. Artificial intelligence in radiation oncology. Nat Rev Clin Oncol. 2020 12; 17(12):771-781.
    View in: PubMed
    Score: 0.229
  8. The impact of quantitative CT-based tumor volumetric features on the outcomes of patients with limited stage small cell lung cancer. Radiat Oncol. 2020 Jan 14; 15(1):14.
    View in: PubMed
    Score: 0.219
  9. Handcrafted versus deep learning radiomics for prediction of cancer therapy response. Lancet Digit Health. 2019 07; 1(3):e106-e107.
    View in: PubMed
    Score: 0.211
  10. Cardiac Radiation Dose, Cardiac Disease, and Mortality in Patients With Lung Cancer. J Am Coll Cardiol. 2019 06 18; 73(23):2976-2987.
    View in: PubMed
    Score: 0.211
  11. Use of Crowd Innovation to Develop an Artificial Intelligence-Based Solution for Radiation Therapy Targeting. JAMA Oncol. 2019 May 01; 5(5):654-661.
    View in: PubMed
    Score: 0.209
  12. Deep Learning Predicts Lung Cancer Treatment Response from Serial Medical Imaging. Clin Cancer Res. 2019 06 01; 25(11):3266-3275.
    View in: PubMed
    Score: 0.208
  13. Artificial intelligence in cancer imaging: Clinical challenges and applications. CA Cancer J Clin. 2019 03; 69(2):127-157.
    View in: PubMed
    Score: 0.205
  14. Deep learning for lung cancer prognostication: A retrospective multi-cohort radiomics study. PLoS Med. 2018 11; 15(11):e1002711.
    View in: PubMed
    Score: 0.203
  15. Peritumoral radiomics features predict distant metastasis in locally advanced NSCLC. PLoS One. 2018; 13(11):e0206108.
    View in: PubMed
    Score: 0.202
  16. Clinical Outcomes After Lung Stereotactic Body Radiation Therapy in Patients With or Without a Prior Lung Resection. Am J Clin Oncol. 2018 07; 41(7):695-701.
    View in: PubMed
    Score: 0.197
  17. Impact of experimental design on PET radiomics in predicting somatic mutation status. Eur J Radiol. 2017 Dec; 97:8-15.
    View in: PubMed
    Score: 0.187
  18. Somatic Mutations Drive Distinct Imaging Phenotypes in Lung Cancer. Cancer Res. 2017 07 15; 77(14):3922-3930.
    View in: PubMed
    Score: 0.183
  19. Lymph node volume predicts survival but not nodal clearance in Stage IIIA-IIIB NSCLC. PLoS One. 2017; 12(4):e0174268.
    View in: PubMed
    Score: 0.181
  20. Associations of Radiomic Data Extracted from Static and Respiratory-Gated CT Scans with Disease Recurrence in Lung Cancer Patients Treated with SBRT. PLoS One. 2017; 12(1):e0169172.
    View in: PubMed
    Score: 0.178
  21. Radiomic-Based Pathological Response Prediction from Primary Tumors and Lymph Nodes in NSCLC. J Thorac Oncol. 2017 03; 12(3):467-476.
    View in: PubMed
    Score: 0.176
  22. Radiologic-pathologic correlation of response to chemoradiation in resectable locally advanced NSCLC. Lung Cancer. 2016 12; 102:1-8.
    View in: PubMed
    Score: 0.175
  23. Inter-scan and inter-observer tumour volume delineation variability on cone beam computed tomography in patients treated with stereotactic body radiation therapy for early-stage non-small cell lung cancer. J Med Imaging Radiat Oncol. 2017 Feb; 61(1):93-98.
    View in: PubMed
    Score: 0.175
  24. Associations Between Somatic Mutations and Metabolic Imaging Phenotypes in Non-Small Cell Lung Cancer. J Nucl Med. 2017 04; 58(4):569-576.
    View in: PubMed
    Score: 0.175
  25. CT-based radiomic analysis of stereotactic body radiation therapy patients with lung cancer. Radiother Oncol. 2016 08; 120(2):258-66.
    View in: PubMed
    Score: 0.171
  26. TU-D-207B-06: Pathological Response Prediction by Radiomic Data From Primary and Lymph Nodes in NSCLC. Med Phys. 2016 Jun; 43(6):3751.
    View in: PubMed
    Score: 0.171
  27. SU-F-R-52: A Comparison of the Performance of Radiomic Features From Free Breathing and 4DCT Scans in Predicting Disease Recurrence in Lung Cancer SBRT Patients. Med Phys. 2016 Jun; 43(6):3385.
    View in: PubMed
    Score: 0.171
  28. SU-D-207B-03: A PET-CT Radiomics Comparison to Predict Distant Metastasis in Lung Adenocarcinoma. Med Phys. 2016 Jun; 43(6):3349.
    View in: PubMed
    Score: 0.171
  29. MO-DE-207B-01: JACK FOWLER JUNIOR INVESTIGATOR COMPETITION WINNER: Between Somatic Mutations and PET-Based Radiomic Features in Non-Small Cell Lung Cancer. Med Phys. 2016 Jun; 43(6):3704.
    View in: PubMed
    Score: 0.171
  30. SU-F-R-53: CT-Based Radiomics Analysis of Non-Small Cell Lung Cancer Patients Treated with Stereotactic Body Radiation Therapy. Med Phys. 2016 Jun; 43(6):3385.
    View in: PubMed
    Score: 0.171
  31. Radiomic phenotype features predict pathological response in non-small cell lung cancer. Radiother Oncol. 2016 06; 119(3):480-6.
    View in: PubMed
    Score: 0.169
  32. Exploratory Study to Identify Radiomics Classifiers for Lung Cancer Histology. Front Oncol. 2016; 6:71.
    View in: PubMed
    Score: 0.169
  33. SU-E-J-246: CT-Based Volumetric Features Are Associated with Somatic Mutations in Lung Cancer. Med Phys. 2015 Jun; 42(6):3322.
    View in: PubMed
    Score: 0.159
  34. SU-E-J-266: Cone Beam Computed Tomography (CBCT) Inter-Scan and Inter-Observer Tumor Volume Variability Assessment in Patients Treated with Stereotactic Body Radiation Therapy (SBRT) for Early Stage Non-Small Cell Lung Cancer (NSCLC). Med Phys. 2015 Jun; 42(6):3328.
    View in: PubMed
    Score: 0.159
  35. CT-based radiomic signature predicts distant metastasis in lung adenocarcinoma. Radiother Oncol. 2015 Mar; 114(3):345-50.
    View in: PubMed
    Score: 0.156
  36. Outcomes by tumor histology and KRAS mutation status after lung stereotactic body radiation therapy for early-stage non-small-cell lung cancer. Clin Lung Cancer. 2015 Jan; 16(1):24-32.
    View in: PubMed
    Score: 0.152
  37. Robust Radiomics feature quantification using semiautomatic volumetric segmentation. PLoS One. 2014; 9(7):e102107.
    View in: PubMed
    Score: 0.150
  38. Volumetric CT-based segmentation of NSCLC using 3D-Slicer. Sci Rep. 2013 Dec 18; 3:3529.
    View in: PubMed
    Score: 0.144
  39. T-staging pulmonary oncology from radiological reports using natural language processing: translating into a multi-language setting. Insights Imaging. 2021 Jun 10; 12(1):77.
    View in: PubMed
    Score: 0.060
  40. Changes in Length and Complexity of Clinical Practice Guidelines in Oncology, 1996-2019. JAMA Netw Open. 2020 03 02; 3(3):e200841.
    View in: PubMed
    Score: 0.055
Connection Strength
The connection strength for co-authors is the sum of the scores for each of their shared publications.

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Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.