29 related articles for article (PubMed ID: 33207877)
1. Identification of diagnostic metabolic signatures in clear cell renal cell carcinoma using mass spectrometry imaging.
Vijayalakshmi K; Shankar V; Bain RM; Nolley R; Sonn GA; Kao CS; Zhao H; Tibshirani R; Zare RN; Brooks JD
Int J Cancer; 2020 Jul; 147(1):256-265. PubMed ID: 31863456
[TBL] [Abstract][Full Text] [Related]
2. Label-Free SERS of Urine Components: A Powerful Tool for Discriminating Renal Cell Carcinoma through Multivariate Analysis and Machine Learning Techniques.
Buhas BA; Toma V; Beauval JB; Andras I; Couți R; Muntean LA; Coman RT; Maghiar TA; Știufiuc RI; Lucaciu CM; Crisan N
Int J Mol Sci; 2024 Mar; 25(7):. PubMed ID: 38612705
[TBL] [Abstract][Full Text] [Related]
3. Wide-Targeted Semi-Quantitative Analysis of Acidic Glycosphingolipids in Cell Lines and Urine to Develop Potential Screening Biomarkers for Renal Cell Carcinoma.
Maekawa M; Sato T; Kanno C; Sakamoto I; Kawasaki Y; Ito A; Mano N
Int J Mol Sci; 2024 Apr; 25(7):. PubMed ID: 38612906
[TBL] [Abstract][Full Text] [Related]
4. Integrating machine learning and nontargeted plasma lipidomics to explore lipid characteristics of premetabolic syndrome and metabolic syndrome.
Huang X; He Q; Hu H; Shi H; Zhang X; Xu Y
Front Endocrinol (Lausanne); 2024; 15():1335269. PubMed ID: 38559697
[TBL] [Abstract][Full Text] [Related]
5. Targeted quantitative lipidomic uncovers lipid biomarkers for predicting the presence of compensated cirrhosis and discriminating decompensated cirrhosis from compensated cirrhosis.
Zeng Y; Zhang L; Zheng Z; Su J; Fu Y; Chen T; Lin K; Liu C; Huang H; Ou Q; Zeng Y
Clin Chem Lab Med; 2024 Feb; 62(3):506-521. PubMed ID: 37924531
[TBL] [Abstract][Full Text] [Related]
6. Discovery of lipid biomarkers correlated with disease progression in clear cell renal cell carcinoma using desorption electrospray ionization imaging mass spectrometry.
Tamura K; Horikawa M; Sato S; Miyake H; Setou M
Oncotarget; 2019 Mar; 10(18):1688-1703. PubMed ID: 30899441
[TBL] [Abstract][Full Text] [Related]
7. Influence of Dietary Polyunsaturated Fatty Acid Intake on Potential Lipid Metabolite Diagnostic Markers in Renal Cell Carcinoma: A Case-Control Study.
Kim YH; Chung JS; Lee HH; Park JH; Kim MK
Nutrients; 2024 Apr; 16(9):. PubMed ID: 38732512
[TBL] [Abstract][Full Text] [Related]
8. Novel research and future prospects of artificial intelligence in cancer diagnosis and treatment.
Zhang C; Xu J; Tang R; Yang J; Wang W; Yu X; Shi S
J Hematol Oncol; 2023 Nov; 16(1):114. PubMed ID: 38012673
[TBL] [Abstract][Full Text] [Related]
9. Fatty acid metabolism reprogramming in ccRCC: mechanisms and potential targets.
Tan SK; Hougen HY; Merchan JR; Gonzalgo ML; Welford SM
Nat Rev Urol; 2023 Jan; 20(1):48-60. PubMed ID: 36192502
[TBL] [Abstract][Full Text] [Related]
10. Epidemiology and Prevention of Renal Cell Carcinoma.
Makino T; Kadomoto S; Izumi K; Mizokami A
Cancers (Basel); 2022 Aug; 14(16):. PubMed ID: 36011051
[TBL] [Abstract][Full Text] [Related]
11. The Diagnostic Value of Serum Ang, VEGF, and CRP Combined with the Chinese Medicine Antitumor Formula in the Treatment of Advanced Renal Carcinoma.
Dong N; Zhang S; Zhang S; Zhao Q; Zhang D; Chen F
Evid Based Complement Alternat Med; 2021; 2021():5189069. PubMed ID: 34950214
[TBL] [Abstract][Full Text] [Related]
12. Urine-Based Metabolomics and Machine Learning Reveals Metabolites Associated with Renal Cell Carcinoma Stage.
Bifarin OO; Gaul DA; Sah S; Arnold RS; Ogan K; Master VA; Roberts DL; Bergquist SH; Petros JA; Edison AS; Fernández FM
Cancers (Basel); 2021 Dec; 13(24):. PubMed ID: 34944874
[TBL] [Abstract][Full Text] [Related]
13. Improved Discrimination of Disease States Using Proteomics Data with the Updated Aristotle Classifier.
Hua D; Desaire H
J Proteome Res; 2021 May; 20(5):2823-2829. PubMed ID: 33909976
[TBL] [Abstract][Full Text] [Related]
14. Coupled Mass-Spectrometry-Based Lipidomics Machine Learning Approach for Early Detection of Clear Cell Renal Cell Carcinoma.
Manzi M; Palazzo M; Knott ME; Beauseroy P; Yankilevich P; Giménez MI; Monge ME
J Proteome Res; 2021 Jan; 20(1):841-857. PubMed ID: 33207877
[TBL] [Abstract][Full Text] [Related]
15. Metabolic Footprinting of a Clear Cell Renal Cell Carcinoma in Vitro Model for Human Kidney Cancer Detection.
Knott ME; Manzi M; Zabalegui N; Salazar MO; Puricelli LI; Monge ME
J Proteome Res; 2018 Nov; 17(11):3877-3888. PubMed ID: 30260228
[TBL] [Abstract][Full Text] [Related]
16. Clinical use of a machine learning histopathological image signature in diagnosis and survival prediction of clear cell renal cell carcinoma.
Chen S; Zhang N; Jiang L; Gao F; Shao J; Wang T; Zhang E; Yu H; Wang X; Zheng J
Int J Cancer; 2021 Feb; 148(3):780-790. PubMed ID: 32895914
[TBL] [Abstract][Full Text] [Related]
17. Postoperative Metabolic Phenoreversion in Clear Cell Renal Cell Carcinoma.
Manzi M; Zabalegui N; Monge ME
J Proteome Res; 2023 Jan; 22(1):1-15. PubMed ID: 36484409
[TBL] [Abstract][Full Text] [Related]
18. Revealing potential lipid biomarkers in clear cell renal cell carcinoma using targeted quantitative lipidomics.
Li W; Wang X; Zhang X; Gong P; Ding D; Wang N; Wang Z
Lipids Health Dis; 2021 Nov; 20(1):160. PubMed ID: 34774030
[TBL] [Abstract][Full Text] [Related]
19. Diagnostic and prognostic tissuemarkers in clear cell and papillary renal cell carcinoma.
Kroeze SG; Bijenhof AM; Bosch JL; Jans JJ
Cancer Biomark; 2010; 7(6):261-8. PubMed ID: 21694464
[TBL] [Abstract][Full Text] [Related]
20.
; ; . PubMed ID:
[No Abstract] [Full Text] [Related]
[Next] [New Search]