204 related articles for article (PubMed ID: 36199694)
41. Radiomic and Dosiomic Features for the Prediction of Radiation Pneumonitis Across Esophageal Cancer and Lung Cancer.
Puttanawarut C; Sirirutbunkajorn N; Tawong N; Jiarpinitnun C; Khachonkham S; Pattaranutaporn P; Wongsawat Y
Front Oncol; 2022; 12():768152. PubMed ID: 35251959
[TBL] [Abstract][Full Text] [Related]
42. Computer-aided diagnosis of ground glass pulmonary nodule by fusing deep learning and radiomics features.
Hu X; Gong J; Zhou W; Li H; Wang S; Wei M; Peng W; Gu Y
Phys Med Biol; 2021 Mar; 66(6):065015. PubMed ID: 33596552
[TBL] [Abstract][Full Text] [Related]
43. The utility of quantitative CT radiomics features for improved prediction of radiation pneumonitis.
Krafft SP; Rao A; Stingo F; Briere TM; Court LE; Liao Z; Martel MK
Med Phys; 2018 Nov; 45(11):5317-5324. PubMed ID: 30133809
[TBL] [Abstract][Full Text] [Related]
44. Predicting acute radiation induced xerostomia in head and neck Cancer using MR and CT Radiomics of parotid and submandibular glands.
Sheikh K; Lee SH; Cheng Z; Lakshminarayanan P; Peng L; Han P; McNutt TR; Quon H; Lee J
Radiat Oncol; 2019 Jul; 14(1):131. PubMed ID: 31358029
[TBL] [Abstract][Full Text] [Related]
45. Computed Tomography-Based Delta-Radiomics Analysis for Discriminating Radiation Pneumonitis in Patients With Esophageal Cancer After Radiation Therapy.
Wang L; Gao Z; Li C; Sun L; Li J; Yu J; Meng X
Int J Radiat Oncol Biol Phys; 2021 Oct; 111(2):443-455. PubMed ID: 33974887
[TBL] [Abstract][Full Text] [Related]
46. Intermediate Dose-Volume Parameters, Not Low-Dose Bath, Is Superior to Predict Radiation Pneumonitis for Lung Cancer Treated With Intensity-Modulated Radiotherapy.
Meng Y; Luo W; Wang W; Zhou C; Zhou S; Tang X; Hou L; Kong FS; Yang H
Front Oncol; 2020; 10():584756. PubMed ID: 33178612
[TBL] [Abstract][Full Text] [Related]
47. Machine learning-based radiomic models to predict intensity-modulated radiation therapy response, Gleason score and stage in prostate cancer.
Abdollahi H; Mofid B; Shiri I; Razzaghdoust A; Saadipoor A; Mahdavi A; Galandooz HM; Mahdavi SR
Radiol Med; 2019 Jun; 124(6):555-567. PubMed ID: 30607868
[TBL] [Abstract][Full Text] [Related]
48. Predicting Adverse Radiation Effects in Brain Tumors After Stereotactic Radiotherapy With Deep Learning and Handcrafted Radiomics.
Keek SA; Beuque M; Primakov S; Woodruff HC; Chatterjee A; van Timmeren JE; Vallières M; Hendriks LEL; Kraft J; Andratschke N; Braunstein SE; Morin O; Lambin P
Front Oncol; 2022; 12():920393. PubMed ID: 35912214
[TBL] [Abstract][Full Text] [Related]
49. A little to a lot or a lot to a little? An analysis of pneumonitis risk from dose-volume histogram parameters of the lung in patients with lung cancer treated with 3-D conformal radiotherapy.
Willner J; Jost A; Baier K; Flentje M
Strahlenther Onkol; 2003 Aug; 179(8):548-56. PubMed ID: 14509954
[TBL] [Abstract][Full Text] [Related]
50. Imbalanced Data Correction Based PET/CT Radiomics Model for Predicting Lymph Node Metastasis in Clinical Stage T1 Lung Adenocarcinoma.
Lv J; Chen X; Liu X; Du D; Lv W; Lu L; Wu H
Front Oncol; 2022; 12():788968. PubMed ID: 35155231
[TBL] [Abstract][Full Text] [Related]
51. A Transfer Learning Framework for Deep Learning-Based CT-to-Perfusion Mapping on Lung Cancer Patients.
Ren G; Li B; Lam SK; Xiao H; Huang YH; Cheung AL; Lu Y; Mao R; Ge H; Kong FS; Ho WY; Cai J
Front Oncol; 2022; 12():883516. PubMed ID: 35847874
[TBL] [Abstract][Full Text] [Related]
52. External validation of radiomics-based predictive models in low-dose CT screening for early lung cancer diagnosis.
Garau N; Paganelli C; Summers P; Choi W; Alam S; Lu W; Fanciullo C; Bellomi M; Baroni G; Rampinelli C
Med Phys; 2020 Sep; 47(9):4125-4136. PubMed ID: 32488865
[TBL] [Abstract][Full Text] [Related]
53. Application and Clinical Value of Machine Learning-Based Cervical Cancer Diagnosis and Prediction Model in Adjuvant Chemotherapy for Cervical Cancer: A Single-Center, Controlled, Non-Arbitrary Size Case-Control Study.
Wang Y; Shen L; Jin J; Wang G
Contrast Media Mol Imaging; 2022; 2022():2432291. PubMed ID: 35821886
[TBL] [Abstract][Full Text] [Related]
54. Correlation of Functional Lung Heterogeneity and Dosimetry to Radiation Pneumonitis using Perfusion SPECT/CT and FDG PET/CT Imaging.
Lee HJ; Zeng J; Vesselle HJ; Patel SA; Rengan R; Bowen SR
Int J Radiat Oncol Biol Phys; 2018 Nov; 102(4):1255-1264. PubMed ID: 30108002
[TBL] [Abstract][Full Text] [Related]
55. Enhanced CT-Based Radiomics to Predict Micropapillary Pattern Within Lung Invasive Adenocarcinoma.
Xu Y; Ji W; Hou L; Lin S; Shi Y; Zhou C; Meng Y; Wang W; Chen X; Wang M; Yang H
Front Oncol; 2021; 11():704994. PubMed ID: 34513686
[TBL] [Abstract][Full Text] [Related]
56. Intratumoral and peritumoral CT-based radiomics strategy reveals distinct subtypes of non-small-cell lung cancer.
Tang X; Huang H; Du P; Wang L; Yin H; Xu X
J Cancer Res Clin Oncol; 2022 Sep; 148(9):2247-2260. PubMed ID: 35430688
[TBL] [Abstract][Full Text] [Related]
57. Use of radiomics based on
Zhou Y; Ma XL; Zhang T; Wang J; Zhang T; Tian R
Eur J Nucl Med Mol Imaging; 2021 Aug; 48(9):2904-2913. PubMed ID: 33547553
[TBL] [Abstract][Full Text] [Related]
58. Radiomics study for predicting the expression of PD-L1 in non-small cell lung cancer based on CT images and clinicopathologic features.
Sun Z; Hu S; Ge Y; Wang J; Duan S; Song J; Hu C; Li Y
J Xray Sci Technol; 2020; 28(3):449-459. PubMed ID: 32176676
[TBL] [Abstract][Full Text] [Related]
59. Receiver operating characteristic curves to assess predictors of radiation-induced symptomatic lung injury.
Lind PA; Marks LB; Hollis D; Fan M; Zhou SM; Munley MT; Shafman TD; Jaszczak RJ; Coleman RE
Int J Radiat Oncol Biol Phys; 2002 Oct; 54(2):340-7. PubMed ID: 12243806
[TBL] [Abstract][Full Text] [Related]
60. PET/CT Based EGFR Mutation Status Classification of NSCLC Using Deep Learning Features and Radiomics Features.
Huang W; Wang J; Wang H; Zhang Y; Zhao F; Li K; Su L; Kang F; Cao X
Front Pharmacol; 2022; 13():898529. PubMed ID: 35571081
[No Abstract] [Full Text] [Related]
[Previous] [Next] [New Search]
