128 related articles for article (PubMed ID: 35237892)
1. Incorporating Radiomics into Machine Learning Models to Predict Outcomes of Neuroblastoma.
Liu G; Poon M; Zapala MA; Temple WC; Vo KT; Matthay KK; Mitra D; Seo Y
J Digit Imaging; 2022 Jun; 35(3):605-612. PubMed ID: 35237892
[TBL] [Abstract][Full Text] [Related]
2. CT-based morphologic and radiomics features for the classification of MYCN gene amplification status in pediatric neuroblastoma.
Tan E; Merchant K; Kn BP; Cs A; Zhao JJ; Saffari SE; Tan PH; Tang PH
Childs Nerv Syst; 2022 Aug; 38(8):1487-1495. PubMed ID: 35460355
[TBL] [Abstract][Full Text] [Related]
3. Prediction for Mitosis-Karyorrhexis Index Status of Pediatric Neuroblastoma via Machine Learning Based
Feng L; Qian L; Yang S; Ren Q; Zhang S; Qin H; Wang W; Wang C; Zhang H; Yang J
Diagnostics (Basel); 2022 Jan; 12(2):. PubMed ID: 35204353
[TBL] [Abstract][Full Text] [Related]
4. Radiogenomics of neuroblastoma in pediatric patients: CT-based radiomics signature in predicting MYCN amplification.
Wu H; Wu C; Zheng H; Wang L; Guan W; Duan S; Wang D
Eur Radiol; 2021 May; 31(5):3080-3089. PubMed ID: 33118047
[TBL] [Abstract][Full Text] [Related]
5. CT-Based Radiomics Signature With Machine Learning Predicts MYCN Amplification in Pediatric Abdominal Neuroblastoma.
Chen X; Wang H; Huang K; Liu H; Ding H; Zhang L; Zhang T; Yu W; He L
Front Oncol; 2021; 11():687884. PubMed ID: 34109133
[TBL] [Abstract][Full Text] [Related]
6. Preoperative classification of primary and metastatic liver cancer via machine learning-based ultrasound radiomics.
Mao B; Ma J; Duan S; Xia Y; Tao Y; Zhang L
Eur Radiol; 2021 Jul; 31(7):4576-4586. PubMed ID: 33447862
[TBL] [Abstract][Full Text] [Related]
7. Prediction of High-Risk Neuroblastoma Among Neuroblastic Tumors Using Radiomics Features Derived from Magnetic Resonance Imaging: A Pilot Study.
Kim J; Choi YH; Yoon H; Lim HJ; Han JW; Lee MJ
Yonsei Med J; 2024 May; 65(5):293-301. PubMed ID: 38653568
[TBL] [Abstract][Full Text] [Related]
8. Optimizing the radiomics-machine-learning model based on non-contrast enhanced CT for the simplified risk categorization of thymic epithelial tumors: A large cohort retrospective study.
Feng XL; Wang SZ; Chen HH; Huang YX; Xin YK; Zhang T; Cheng DL; Mao L; Li XL; Liu CX; Hu YC; Wang W; Cui GB; Nan HY
Lung Cancer; 2022 Apr; 166():150-160. PubMed ID: 35287067
[TBL] [Abstract][Full Text] [Related]
9. Computed Tomography-Based Radiomics Model to Predict Central Cervical Lymph Node Metastases in Papillary Thyroid Carcinoma: A Multicenter Study.
Li J; Wu X; Mao N; Zheng G; Zhang H; Mou Y; Jia C; Mi J; Song X
Front Endocrinol (Lausanne); 2021; 12():741698. PubMed ID: 34745008
[TBL] [Abstract][Full Text] [Related]
10. Role of MRI radiomics for the prediction of MYCN amplification in neuroblastomas.
Ghosh A; Yekeler E; Teixeira SR; Dalal D; States L
Eur Radiol; 2023 Oct; 33(10):6726-6735. PubMed ID: 37178203
[TBL] [Abstract][Full Text] [Related]
11. Radiomics-based machine learning model to predict risk of death within 5-years in clear cell renal cell carcinoma patients.
Nazari M; Shiri I; Zaidi H
Comput Biol Med; 2021 Feb; 129():104135. PubMed ID: 33254045
[TBL] [Abstract][Full Text] [Related]
12. Radiogenomics prediction for MYCN amplification in neuroblastoma: A hypothesis generating study.
Di Giannatale A; Di Paolo PL; Curione D; Lenkowicz J; Napolitano A; Secinaro A; Tomà P; Locatelli F; Castellano A; Boldrini L
Pediatr Blood Cancer; 2021 Sep; 68(9):e29110. PubMed ID: 34003574
[TBL] [Abstract][Full Text] [Related]
13. Next-Generation Radiogenomics Sequencing for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients Using Multimodal Imaging and Machine Learning Algorithms.
Shiri I; Maleki H; Hajianfar G; Abdollahi H; Ashrafinia S; Hatt M; Zaidi H; Oveisi M; Rahmim A
Mol Imaging Biol; 2020 Aug; 22(4):1132-1148. PubMed ID: 32185618
[TBL] [Abstract][Full Text] [Related]
14. An investigation of machine learning methods in delta-radiomics feature analysis.
Chang Y; Lafata K; Sun W; Wang C; Chang Z; Kirkpatrick JP; Yin FF
PLoS One; 2019; 14(12):e0226348. PubMed ID: 31834910
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. Clinical parameters combined with radiomics features of PET/CT can predict recurrence in patients with high-risk pediatric neuroblastoma.
Feng L; Qian L; Yang S; Ren Q; Zhang S; Qin H; Wang W; Wang C; Zhang H; Yang J
BMC Med Imaging; 2022 May; 22(1):102. PubMed ID: 35643445
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Application of machine learning model to predict osteoporosis based on abdominal computed tomography images of the psoas muscle: a retrospective study.
Huang CB; Hu JS; Tan K; Zhang W; Xu TH; Yang L
BMC Geriatr; 2022 Oct; 22(1):796. PubMed ID: 36229793
[TBL] [Abstract][Full Text] [Related]
19. Non-contrast Cine Cardiac Magnetic Resonance image radiomics features and machine learning algorithms for myocardial infarction detection.
Avard E; Shiri I; Hajianfar G; Abdollahi H; Kalantari KR; Houshmand G; Kasani K; Bitarafan-Rajabi A; Deevband MR; Oveisi M; Zaidi H
Comput Biol Med; 2022 Feb; 141():105145. PubMed ID: 34929466
[TBL] [Abstract][Full Text] [Related]
20. Machine learning-based Radiomics analysis for differentiation degree and lymphatic node metastasis of extrahepatic cholangiocarcinoma.
Tang Y; Yang CM; Su S; Wang WJ; Fan LP; Shu J
BMC Cancer; 2021 Nov; 21(1):1268. PubMed ID: 34819043
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]