These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
176 related articles for article (PubMed ID: 37196386)
1. Deep learning-based PET/MR radiomics for the classification of annualized relapse rate in multiple sclerosis. Du S; Yuan C; Zhou Q; Huang X; Meng H; Chen M; Wang H; Huang Q; Xiang S; Qian D; Li B; Chen S; Zhang M Mult Scler Relat Disord; 2023 Jul; 75():104750. PubMed ID: 37196386 [TBL] [Abstract][Full Text] [Related]
2. Prediction of unenhanced lesion evolution in multiple sclerosis using radiomics-based models: a machine learning approach. Peng Y; Zheng Y; Tan Z; Liu J; Xiang Y; Liu H; Dai L; Xie Y; Wang J; Zeng C; Li Y Mult Scler Relat Disord; 2021 Aug; 53():102989. PubMed ID: 34052741 [TBL] [Abstract][Full Text] [Related]
3. 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]
4. Classification of pulmonary lesion based on multiparametric MRI: utility of radiomics and comparison of machine learning methods. Wang X; Wan Q; Chen H; Li Y; Li X Eur Radiol; 2020 Aug; 30(8):4595-4605. PubMed ID: 32222795 [TBL] [Abstract][Full Text] [Related]
5. Considerable effects of imaging sequences, feature extraction, feature selection, and classifiers on radiomics-based prediction of microvascular invasion in hepatocellular carcinoma using magnetic resonance imaging. Dai H; Lu M; Huang B; Tang M; Pang T; Liao B; Cai H; Huang M; Zhou Y; Chen X; Ding H; Feng ST Quant Imaging Med Surg; 2021 May; 11(5):1836-1853. PubMed ID: 33936969 [TBL] [Abstract][Full Text] [Related]
6. Radiomics analysis for the differentiation of autoimmune pancreatitis and pancreatic ductal adenocarcinoma in Zhang Y; Cheng C; Liu Z; Wang L; Pan G; Sun G; Chang Y; Zuo C; Yang X Med Phys; 2019 Oct; 46(10):4520-4530. PubMed ID: 31348535 [TBL] [Abstract][Full Text] [Related]
7. Deep learning for fully automated tumor segmentation and extraction of magnetic resonance radiomics features in cervical cancer. Lin YC; Lin CH; Lu HY; Chiang HJ; Wang HK; Huang YT; Ng SH; Hong JH; Yen TC; Lai CH; Lin G Eur Radiol; 2020 Mar; 30(3):1297-1305. PubMed ID: 31712961 [TBL] [Abstract][Full Text] [Related]
8. Fully automated segmentation and radiomics feature extraction of hypopharyngeal cancer on MRI using deep learning. Lin YC; Lin G; Pandey S; Yeh CH; Wang JJ; Lin CY; Ho TY; Ko SF; Ng SH Eur Radiol; 2023 Sep; 33(9):6548-6556. PubMed ID: 37338554 [TBL] [Abstract][Full Text] [Related]
9. 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]
10. A subregion-based positron emission tomography/computed tomography (PET/CT) radiomics model for the classification of non-small cell lung cancer histopathological subtypes. Shen H; Chen L; Liu K; Zhao K; Li J; Yu L; Ye H; Zhu W Quant Imaging Med Surg; 2021 Jul; 11(7):2918-2932. PubMed ID: 34249623 [TBL] [Abstract][Full Text] [Related]
11. A multidomain fusion model of radiomics and deep learning to discriminate between PDAC and AIP based on Wei W; Jia G; Wu Z; Wang T; Wang H; Wei K; Cheng C; Liu Z; Zuo C Jpn J Radiol; 2023 Apr; 41(4):417-427. PubMed ID: 36409398 [TBL] [Abstract][Full Text] [Related]
12. Joint MRI T1 Unenhancing and Contrast-enhancing Multiple Sclerosis Lesion Segmentation with Deep Learning in OPERA Trials. Krishnan AP; Song Z; Clayton D; Gaetano L; Jia X; de Crespigny A; Bengtsson T; Carano RAD Radiology; 2022 Mar; 302(3):662-673. PubMed ID: 34904871 [TBL] [Abstract][Full Text] [Related]
13. Multi-lesion radiomics model for discrimination of relapsing-remitting multiple sclerosis and neuropsychiatric systemic lupus erythematosus. Luo X; Piao S; Li H; Li Y; Xia W; Bao Y; Liu X; Geng D; Wu H; Yang L Eur Radiol; 2022 Aug; 32(8):5700-5710. PubMed ID: 35243524 [TBL] [Abstract][Full Text] [Related]
14. Integrating Clinical Data and Radiomics and Deep Learning Features for End-to-End Delayed Cerebral Ischemia Prediction on Noncontrast CT. Ban QQ; Zhang HT; Wang W; Du YF; Zhao Y; Peng AJ; Qu H AJNR Am J Neuroradiol; 2024 Sep; 45(9):1260-1268. PubMed ID: 39025637 [TBL] [Abstract][Full Text] [Related]
15. Automated prediction of the neoadjuvant chemotherapy response in osteosarcoma with deep learning and an MRI-based radiomics nomogram. Zhong J; Zhang C; Hu Y; Zhang J; Liu Y; Si L; Xing Y; Ding D; Geng J; Jiao Q; Zhang H; Yang G; Yao W Eur Radiol; 2022 Sep; 32(9):6196-6206. PubMed ID: 35364712 [TBL] [Abstract][Full Text] [Related]
16. SVM recursive feature elimination analyses of structural brain MRI predicts near-term relapses in patients with clinically isolated syndromes suggestive of multiple sclerosis. Wottschel V; Chard DT; Enzinger C; Filippi M; Frederiksen JL; Gasperini C; Giorgio A; Rocca MA; Rovira A; De Stefano N; Tintoré M; Alexander DC; Barkhof F; Ciccarelli O; Neuroimage Clin; 2019; 24():102011. PubMed ID: 31734524 [TBL] [Abstract][Full Text] [Related]
17. IDH1 mutation prediction using MR-based radiomics in glioblastoma: comparison between manual and fully automated deep learning-based approach of tumor segmentation. Choi Y; Nam Y; Lee YS; Kim J; Ahn KJ; Jang J; Shin NY; Kim BS; Jeon SS Eur J Radiol; 2020 Jul; 128():109031. PubMed ID: 32417712 [TBL] [Abstract][Full Text] [Related]
18. Introducing radiomics model to predict active plaque in multiple sclerosis patients using magnetic resonance images. Khajetash B; Talebi A; Bagherpour Z; Abbaspour S; Tavakoli M Biomed Phys Eng Express; 2023 Jul; 9(5):. PubMed ID: 37379814 [TBL] [Abstract][Full Text] [Related]
19. Deep learning-based automatic segmentation of meningioma from multiparametric MRI for preoperative meningioma differentiation using radiomic features: a multicentre study. Chen H; Li S; Zhang Y; Liu L; Lv X; Yi Y; Ruan G; Ke C; Feng Y Eur Radiol; 2022 Oct; 32(10):7248-7259. PubMed ID: 35420299 [TBL] [Abstract][Full Text] [Related]
20. A comparative study between deep learning and radiomics models in grading liver tumors using hepatobiliary phase contrast-enhanced MR images. Du L; Yuan J; Gan M; Li Z; Wang P; Hou Z; Wang C BMC Med Imaging; 2022 Dec; 22(1):218. PubMed ID: 36517762 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]