150 related articles for article (PubMed ID: 37720416)
1. Development of a Radiomics-Based Model to Predict Graft Fibrosis in Liver Transplant Recipients: A Pilot Study.
Qazi Arisar FA; Salinas-Miranda E; Ale Ali H; Lajkosz K; Chen C; Azhie A; Healy GM; Deniffel D; Haider MA; Bhat M
Transpl Int; 2023; 36():11149. PubMed ID: 37720416
[TBL] [Abstract][Full Text] [Related]
2. Combining Hepatic and Splenic CT Radiomic Features Improves Radiomic Analysis Performance for Liver Fibrosis Staging.
Yin Y; Yakar D; Dierckx RAJO; Mouridsen KB; Kwee TC; de Haas RJ
Diagnostics (Basel); 2022 Feb; 12(2):. PubMed ID: 35204639
[No Abstract] [Full Text] [Related]
3. Radiomic analysis for early differentiation of lung cancer recurrence from fibrosis in patients treated with lung stereotactic ablative radiotherapy.
Kunkyab T; Mou B; Jirasek A; Haston C; Andrews J; Thomas S; Hyde D
Phys Med Biol; 2023 Aug; 68(16):. PubMed ID: 37164024
[No Abstract] [Full Text] [Related]
4. A Pre-TACE Radiomics Model to Predict HCC Progression and Recurrence in Liver Transplantation: A Pilot Study on a Novel Biomarker.
Ivanics T; Salinas-Miranda E; Abreu P; Khalvati F; Namdar K; Dong X; Deniffel D; Gorgen A; Erdman L; Jhaveri K; Haider M; Veit-Haibach P; Sapisochin G
Transplantation; 2021 Nov; 105(11):2435-2444. PubMed ID: 33982917
[TBL] [Abstract][Full Text] [Related]
5. Artificial intelligence for predicting survival following deceased donor liver transplantation: Retrospective multi-center study.
Yu YD; Lee KS; Man Kim J; Ryu JH; Lee JG; Lee KW; Kim BW; Kim DS;
Int J Surg; 2022 Sep; 105():106838. PubMed ID: 36028137
[TBL] [Abstract][Full Text] [Related]
6. A Machine Learning Model Based on PET/CT Radiomics and Clinical Characteristics Predicts ALK Rearrangement Status in Lung Adenocarcinoma.
Chang C; Sun X; Wang G; Yu H; Zhao W; Ge Y; Duan S; Qian X; Wang R; Lei B; Wang L; Liu L; Ruan M; Yan H; Liu C; Chen J; Xie W
Front Oncol; 2021; 11():603882. PubMed ID: 33738250
[TBL] [Abstract][Full Text] [Related]
7. Radiomics outperforms clinical factors in characterizing human papilloma virus (HPV) for patients with oropharyngeal squamous cell carcinomas.
Bagher-Ebadian H; Siddiqui F; Ghanem AI; Zhu S; Lu M; Movsas B; Chetty IJ
Biomed Phys Eng Express; 2022 Jun; 8(4):. PubMed ID: 34781281
[No Abstract] [Full Text] [Related]
8. Machine Learning-Based CT Radiomics Analysis for Prognostic Prediction in Metastatic Non-Small Cell Lung Cancer Patients With
Tang X; Li Y; Yan WF; Qian WL; Pang T; Gong YL; Yang ZG
Front Oncol; 2021; 11():719919. PubMed ID: 34660285
[TBL] [Abstract][Full Text] [Related]
9. A radiomic-based model of different contrast-enhanced CT phase for differentiate intrahepatic cholangiocarcinoma from inflammatory mass with hepatolithiasis.
Xue B; Wu S; Zhang M; Hong J; Liu B; Xu N; Zeng Q; Tang K; Zheng X
Abdom Radiol (NY); 2021 Aug; 46(8):3835-3844. PubMed ID: 33728532
[TBL] [Abstract][Full Text] [Related]
10. Radiomic analysis of liver grafts from brain-dead donors can predict early allograft dysfunction following transplantation: a proof-of-concept study.
Robin F; Khene ZE; Livin M; Sumner C; Houssel-Debry P; Sulpice L; Boudjema K
HPB (Oxford); 2022 Sep; 24(9):1527-1534. PubMed ID: 35382981
[TBL] [Abstract][Full Text] [Related]
11. Generalization optimizing machine learning to improve CT scan radiomics and assess immune checkpoint inhibitors' response in non-small cell lung cancer: a multicenter cohort study.
Tonneau M; Phan K; Manem VSK; Low-Kam C; Dutil F; Kazandjian S; Vanderweyen D; Panasci J; Malo J; Coulombe F; Gagné A; Elkrief A; Belkaïd W; Di Jorio L; Orain M; Bouchard N; Muanza T; Rybicki FJ; Kafi K; Huntsman D; Joubert P; Chandelier F; Routy B
Front Oncol; 2023; 13():1196414. PubMed ID: 37546399
[TBL] [Abstract][Full Text] [Related]
12. Machine learning-based analysis of CT radiomics model for prediction of colorectal metachronous liver metastases.
Taghavi M; Trebeschi S; Simões R; Meek DB; Beckers RCJ; Lambregts DMJ; Verhoef C; Houwers JB; van der Heide UA; Beets-Tan RGH; Maas M
Abdom Radiol (NY); 2021 Jan; 46(1):249-256. PubMed ID: 32583138
[TBL] [Abstract][Full Text] [Related]
13. Preoperative prediction of vessel invasion in locally advanced gastric cancer based on computed tomography radiomics and machine learning.
Hu ZW; Liang P; Li ZL; Yong LL; Lu H; Wang R; Gao JB
Oncol Lett; 2023 Jul; 26(1):293. PubMed ID: 37274479
[TBL] [Abstract][Full Text] [Related]
14. A radiomic nomogram based on arterial phase of CT for differential diagnosis of ovarian cancer.
Hu Y; Weng Q; Xia H; Chen T; Kong C; Chen W; Pang P; Xu M; Lu C; Ji J
Abdom Radiol (NY); 2021 Jun; 46(6):2384-2392. PubMed ID: 34086094
[TBL] [Abstract][Full Text] [Related]
15. Development of an MRI-Based Radiomics-Clinical Model to Diagnose Liver Fibrosis Secondary to Pancreaticobiliary Maljunction in Children.
Yang Y; Zhang X; Zhao L; Mao H; Cai TN; Guo WL
J Magn Reson Imaging; 2023 Aug; 58(2):605-617. PubMed ID: 36583731
[TBL] [Abstract][Full Text] [Related]
16. Diagnostic performance of 2D-shear wave elastography and serum fibrosis markers for evaluation of hepatic graft fibrosis in pediatric liver-inclusive transplant recipients: A prospective pilot study.
Vo HD; Radio SJ; Granader EJ; Wojkiewicz LE; Turner P; Mauch TJ
Pediatr Transplant; 2022 Jun; 26(4):e14225. PubMed ID: 35005824
[TBL] [Abstract][Full Text] [Related]
17. Technical note: On the development of an outcome-driven frequency filter for improving radiomics-based modeling of human papillomavirus (HPV) in patients with oropharyngeal squamous cell carcinoma.
Bagher-Ebadian H; Zhu S; Siddiqui F; Lu M; Movsas B; Chetty IJ
Med Phys; 2021 Nov; 48(11):7552-7562. PubMed ID: 34390003
[TBL] [Abstract][Full Text] [Related]
18. Clinical-radiomics nomogram for predicting esophagogastric variceal bleeding risk noninvasively in patients with cirrhosis.
Luo R; Gao J; Gan W; Xie WB
World J Gastroenterol; 2023 Feb; 29(6):1076-1089. PubMed ID: 36844133
[TBL] [Abstract][Full Text] [Related]
19. A radiomics approach to assess tumour-infiltrating CD8 cells and response to anti-PD-1 or anti-PD-L1 immunotherapy: an imaging biomarker, retrospective multicohort study.
Sun R; Limkin EJ; Vakalopoulou M; Dercle L; Champiat S; Han SR; Verlingue L; Brandao D; Lancia A; Ammari S; Hollebecque A; Scoazec JY; Marabelle A; Massard C; Soria JC; Robert C; Paragios N; Deutsch E; Ferté C
Lancet Oncol; 2018 Sep; 19(9):1180-1191. PubMed ID: 30120041
[TBL] [Abstract][Full Text] [Related]
20. An imageomics and multi-network based deep learning model for risk assessment of liver transplantation for hepatocellular cancer.
He T; Fong JN; Moore LW; Ezeana CF; Victor D; Divatia M; Vasquez M; Ghobrial RM; Wong STC
Comput Med Imaging Graph; 2021 Apr; 89():101894. PubMed ID: 33725579
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
