738 related articles for article (PubMed ID: 29446758)
1. Localized thin-section CT with radiomics feature extraction and machine learning to classify early-detected pulmonary nodules from lung cancer screening.
Tu SJ; Wang CW; Pan KT; Wu YC; Wu CT
Phys Med Biol; 2018 Mar; 63(6):065005. PubMed ID: 29446758
[TBL] [Abstract][Full Text] [Related]
2. Preoperative diagnosis of malignant pulmonary nodules in lung cancer screening with a radiomics nomogram.
Liu A; Wang Z; Yang Y; Wang J; Dai X; Wang L; Lu Y; Xue F
Cancer Commun (Lond); 2020 Jan; 40(1):16-24. PubMed ID: 32125097
[TBL] [Abstract][Full Text] [Related]
3. Computer-aided diagnosis of lung cancer: the effect of training data sets on classification accuracy of lung nodules.
Gong J; Liu JY; Sun XW; Zheng B; Nie SD
Phys Med Biol; 2018 Feb; 63(3):035036. PubMed ID: 29311420
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. Effect of CT Reconstruction Algorithm on the Diagnostic Performance of Radiomics Models: A Task-Based Approach for Pulmonary Subsolid Nodules.
Kim H; Park CM; Gwak J; Hwang EJ; Lee SY; Jung J; Hong H; Goo JM
AJR Am J Roentgenol; 2019 Mar; 212(3):505-512. PubMed ID: 30476456
[TBL] [Abstract][Full Text] [Related]
6. Assessment of indeterminate pulmonary nodules detected in lung cancer screening: Diagnostic accuracy of FDG PET/CT.
Garcia-Velloso MJ; Bastarrika G; de-Torres JP; Lozano MD; Sanchez-Salcedo P; Sancho L; Nuñez-Cordoba JM; Campo A; Alcaide AB; Torre W; Richter JA; Zulueta JJ
Lung Cancer; 2016 Jul; 97():81-6. PubMed ID: 27237032
[TBL] [Abstract][Full Text] [Related]
7. Added Value of Computer-aided CT Image Features for Early Lung Cancer Diagnosis with Small Pulmonary Nodules: A Matched Case-Control Study.
Huang P; Park S; Yan R; Lee J; Chu LC; Lin CT; Hussien A; Rathmell J; Thomas B; Chen C; Hales R; Ettinger DS; Brock M; Hu P; Fishman EK; Gabrielson E; Lam S
Radiology; 2018 Jan; 286(1):286-295. PubMed ID: 28872442
[TBL] [Abstract][Full Text] [Related]
8. Machine learning-based radiomics strategy for prediction of cell proliferation in non-small cell lung cancer.
Gu Q; Feng Z; Liang Q; Li M; Deng J; Ma M; Wang W; Liu J; Liu P; Rong P
Eur J Radiol; 2019 Sep; 118():32-37. PubMed ID: 31439255
[TBL] [Abstract][Full Text] [Related]
9. A combined non-enhanced CT radiomics and clinical variable machine learning model for differentiating benign and malignant sub-centimeter pulmonary solid nodules.
Lin RY; Zheng YN; Lv FJ; Fu BJ; Li WJ; Liang ZR; Chu ZG
Med Phys; 2023 May; 50(5):2835-2843. PubMed ID: 36810703
[TBL] [Abstract][Full Text] [Related]
10. Machine learning approach for distinguishing malignant and benign lung nodules utilizing standardized perinodular parenchymal features from CT.
Uthoff J; Stephens MJ; Newell JD; Hoffman EA; Larson J; Koehn N; De Stefano FA; Lusk CM; Wenzlaff AS; Watza D; Neslund-Dudas C; Carr LL; Lynch DA; Schwartz AG; Sieren JC
Med Phys; 2019 Jul; 46(7):3207-3216. PubMed ID: 31087332
[TBL] [Abstract][Full Text] [Related]
11. Predicting Malignant Nodules from Screening CT Scans.
Hawkins S; Wang H; Liu Y; Garcia A; Stringfield O; Krewer H; Li Q; Cherezov D; Gatenby RA; Balagurunathan Y; Goldgof D; Schabath MB; Hall L; Gillies RJ
J Thorac Oncol; 2016 Dec; 11(12):2120-2128. PubMed ID: 27422797
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. Joint use of the radiomics method and frozen sections should be considered in the prediction of the final classification of peripheral lung adenocarcinoma manifesting as ground-glass nodules.
Wang B; Tang Y; Chen Y; Hamal P; Zhu Y; Wang T; Sun Y; Lu Y; Bhuva MS; Meng X; Yang Y; Ai Z; Wu C; Sun X
Lung Cancer; 2020 Jan; 139():103-110. PubMed ID: 31760351
[TBL] [Abstract][Full Text] [Related]
14. CT-based radiomics and machine learning to predict spread through air space in lung adenocarcinoma.
Jiang C; Luo Y; Yuan J; You S; Chen Z; Wu M; Wang G; Gong J
Eur Radiol; 2020 Jul; 30(7):4050-4057. PubMed ID: 32112116
[TBL] [Abstract][Full Text] [Related]
15. Effect of CT image acquisition parameters on diagnostic performance of radiomics in predicting malignancy of pulmonary nodules of different sizes.
Xu Y; Lu L; Sun SH; E LN; Lian W; Yang H; Schwartz LH; Yang ZH; Zhao B
Eur Radiol; 2022 Mar; 32(3):1517-1527. PubMed ID: 34549324
[TBL] [Abstract][Full Text] [Related]
16. Combining serum miRNAs, CEA, and CYFRA21-1 with imaging and clinical features to distinguish benign and malignant pulmonary nodules: a pilot study : Xianfeng Li et al.: Combining biomarker, imaging, and clinical features to distinguish pulmonary nodules.
Li X; Zhang Q; Jin X; Cao L
World J Surg Oncol; 2017 May; 15(1):107. PubMed ID: 28545454
[TBL] [Abstract][Full Text] [Related]
17. Predicting malignant potential of subsolid nodules: can radiomics preempt longitudinal follow up CT?
Digumarthy SR; Padole AM; Rastogi S; Price M; Mooradian MJ; Sequist LV; Kalra MK
Cancer Imaging; 2019 Jun; 19(1):36. PubMed ID: 31182167
[TBL] [Abstract][Full Text] [Related]
18. Preoperative CT-based radiomics combined with intraoperative frozen section is predictive of invasive adenocarcinoma in pulmonary nodules: a multicenter study.
Wu G; Woodruff HC; Sanduleanu S; Refaee T; Jochems A; Leijenaar R; Gietema H; Shen J; Wang R; Xiong J; Bian J; Wu J; Lambin P
Eur Radiol; 2020 May; 30(5):2680-2691. PubMed ID: 32006165
[TBL] [Abstract][Full Text] [Related]
19. Development and external validation of a multimodal integrated feature neural network (MIFNN) for the diagnosis of malignancy in small pulmonary nodules (≤10 mm).
Yang R; Zhang Y; Li W; Li Q; Liu X; Zhang F; Liang Z; Huang J; Li X; Tao L; Guo X
Biomed Phys Eng Express; 2024 May; 10(4):. PubMed ID: 38684143
[No Abstract] [Full Text] [Related]
20. Radiomics analysis to predict pulmonary nodule malignancy using machine learning approaches.
Warkentin MT; Al-Sawaihey H; Lam S; Liu G; Diergaarde B; Yuan JM; Wilson DO; Atkar-Khattra S; Grant B; Brhane Y; Khodayari-Moez E; Murison KR; Tammemagi MC; Campbell KR; Hung RJ
Thorax; 2024 Mar; 79(4):307-315. PubMed ID: 38195644
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
