725 related articles for article (PubMed ID: 34872823)
21. Tensor radiomics: paradigm for systematic incorporation of multi-flavoured radiomics features.
Rahmim A; Toosi A; Salmanpour MR; Dubljevic N; Janzen I; Shiri I; Yuan R; Ho C; Zaidi H; MacAulay C; Uribe C; Yousefirizi F
Quant Imaging Med Surg; 2023 Dec; 13(12):7680-7694. PubMed ID: 38106259
[TBL] [Abstract][Full Text] [Related]
22. Potential feature exploration and model development based on 18F-FDG PET/CT images for differentiating benign and malignant lung lesions.
Zhang R; Zhu L; Cai Z; Jiang W; Li J; Yang C; Yu C; Jiang B; Wang W; Xu W; Chai X; Zhang X; Tang Y
Eur J Radiol; 2019 Dec; 121():108735. PubMed ID: 31733432
[TBL] [Abstract][Full Text] [Related]
23. Homology-based radiomic features for prediction of the prognosis of lung cancer based on CT-based radiomics.
Kadoya N; Tanaka S; Kajikawa T; Tanabe S; Abe K; Nakajima Y; Yamamoto T; Takahashi N; Takeda K; Dobashi S; Takeda K; Nakane K; Jingu K
Med Phys; 2020 Jun; 47(5):2197-2205. PubMed ID: 32096876
[TBL] [Abstract][Full Text] [Related]
24. Automated lung tumor delineation on positron emission tomography/computed tomography via a hybrid regional network.
Lei Y; Wang T; Jeong JJ; Janopaul-Naylor J; Kesarwala AH; Roper J; Tian S; Bradley JD; Liu T; Higgins K; Yang X
Med Phys; 2023 Jan; 50(1):274-283. PubMed ID: 36203393
[TBL] [Abstract][Full Text] [Related]
25. A prognostic analysis method for non-small cell lung cancer based on the computed tomography radiomics.
Wang X; Duan H; Li X; Ye X; Huang G; Nie S
Phys Med Biol; 2020 Feb; 65(4):045006. PubMed ID: 31962301
[TBL] [Abstract][Full Text] [Related]
26. Prognostic Value of
Carlier T; Frécon G; Mateus D; Rizkallah M; Kraeber-Bodéré F; Kanoun S; Blanc-Durand P; Itti E; Le Gouill S; Casasnovas RO; Bodet-Milin C; Bailly C
J Nucl Med; 2024 Jan; 65(1):156-162. PubMed ID: 37945379
[TBL] [Abstract][Full Text] [Related]
27. A machine learning approach using
Qi WX; Li S; Xiao J; Li H; Chen J; Zhao S
Front Immunol; 2024; 15():1351750. PubMed ID: 38352868
[TBL] [Abstract][Full Text] [Related]
28. Deep learning radiomics model based on PET/CT predicts PD-L1 expression in non-small cell lung cancer.
Li B; Su J; Liu K; Hu C
Eur J Radiol Open; 2024 Jun; 12():100549. PubMed ID: 38304572
[TBL] [Abstract][Full Text] [Related]
29. A multi-instance tumor subtype classification method for small PET datasets using RA-DL attention module guided deep feature extraction with radiomics features.
Diao Z; Jiang H
Comput Biol Med; 2024 May; 174():108461. PubMed ID: 38626509
[TBL] [Abstract][Full Text] [Related]
30. Efficient 18F-fluorodeoxyglucose positron emission tomography/computed tomography-based machine learning model for predicting epidermal growth factor receptor mutations in non-small cell lung cancer.
Ruan D; Fang J; Teng X
Q J Nucl Med Mol Imaging; 2024 Mar; 68(1):70-83. PubMed ID: 35420272
[TBL] [Abstract][Full Text] [Related]
31. Effect of machine learning methods on predicting NSCLC overall survival time based on Radiomics analysis.
Sun W; Jiang M; Dang J; Chang P; Yin FF
Radiat Oncol; 2018 Oct; 13(1):197. PubMed ID: 30290849
[TBL] [Abstract][Full Text] [Related]
32. Pretreatment
Dissaux G; Visvikis D; Da-Ano R; Pradier O; Chajon E; Barillot I; Duvergé L; Masson I; Abgral R; Santiago Ribeiro MJ; Devillers A; Pallardy A; Fleury V; Mahé MA; De Crevoisier R; Hatt M; Schick U
J Nucl Med; 2020 Jun; 61(6):814-820. PubMed ID: 31732678
[TBL] [Abstract][Full Text] [Related]
33. 18F-fluorodeoxyglucose positron-emission tomography (FDG-PET)-Radiomics of metastatic lymph nodes and primary tumor in non-small cell lung cancer (NSCLC) - A prospective externally validated study.
Carvalho S; Leijenaar RTH; Troost EGC; van Timmeren JE; Oberije C; van Elmpt W; de Geus-Oei LF; Bussink J; Lambin P
PLoS One; 2018; 13(3):e0192859. PubMed ID: 29494598
[TBL] [Abstract][Full Text] [Related]
34. Machine learning based on SPECT/CT to differentiate bone metastasis and benign bone lesions in lung malignancy patients.
Wang H; Chen Y; Qiu J; Xie J; Lu W; Ma J; Jia M
Med Phys; 2024 Apr; 51(4):2578-2588. PubMed ID: 37966123
[TBL] [Abstract][Full Text] [Related]
35. Value of pre-therapy
Zhang J; Zhao X; Zhao Y; Zhang J; Zhang Z; Wang J; Wang Y; Dai M; Han J
Eur J Nucl Med Mol Imaging; 2020 May; 47(5):1137-1146. PubMed ID: 31728587
[TBL] [Abstract][Full Text] [Related]
36. Machine learning for radiomics-based multimodality and multiparametric modeling.
Wei L; Osman S; Hatt M; El Naqa I
Q J Nucl Med Mol Imaging; 2019 Dec; 63(4):323-338. PubMed ID: 31527580
[TBL] [Abstract][Full Text] [Related]
37. Prediction of pathologic stage in non-small cell lung cancer using machine learning algorithm based on CT image feature analysis.
Yu L; Tao G; Zhu L; Wang G; Li Z; Ye J; Chen Q
BMC Cancer; 2019 May; 19(1):464. PubMed ID: 31101024
[TBL] [Abstract][Full Text] [Related]
38. Effects of alterations in positron emission tomography imaging parameters on radiomics features.
Ger RB; Meier JG; Pahlka RB; Gay S; Mumme R; Fuller CD; Li H; Howell RM; Layman RR; Stafford RJ; Zhou S; Mawlawi O; Court LE
PLoS One; 2019; 14(9):e0221877. PubMed ID: 31487307
[TBL] [Abstract][Full Text] [Related]
39. Comparison of radiomics machine-learning classifiers and feature selection for differentiation of sacral chordoma and sacral giant cell tumour based on 3D computed tomography features.
Yin P; Mao N; Zhao C; Wu J; Sun C; Chen L; Hong N
Eur Radiol; 2019 Apr; 29(4):1841-1847. PubMed ID: 30280245
[TBL] [Abstract][Full Text] [Related]
40. Additional value of metabolic parameters to PET/CT-based radiomics nomogram in predicting lymphovascular invasion and outcome in lung adenocarcinoma.
Nie P; Yang G; Wang N; Yan L; Miao W; Duan Y; Wang Y; Gong A; Zhao Y; Wu J; Zhang C; Wang M; Cui J; Yu M; Li D; Sun Y; Wang Y; Wang Z
Eur J Nucl Med Mol Imaging; 2021 Jan; 48(1):217-230. PubMed ID: 32451603
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
