152 related articles for article (PubMed ID: 37868825)
1. Machine Learning Developed a Programmed Cell Death Signature for Predicting Prognosis, Ecosystem, and Drug Sensitivity in Ovarian Cancer.
Wang L; Chen X; Song L; Zou H
Anal Cell Pathol (Amst); 2023; 2023():7365503. PubMed ID: 37868825
[TBL] [Abstract][Full Text] [Related]
2. Machine learning developed a PI3K/Akt pathway-related signature for predicting prognosis and drug sensitivity in ovarian cancer.
Han X; Yang L; Tian H; Ji Y
Aging (Albany NY); 2023 Oct; 15(20):11162-11183. PubMed ID: 37851341
[TBL] [Abstract][Full Text] [Related]
3. A macrophage related signature for predicting prognosis and drug sensitivity in ovarian cancer based on integrative machine learning.
Zhao B; Pei L
BMC Med Genomics; 2023 Oct; 16(1):230. PubMed ID: 37784081
[TBL] [Abstract][Full Text] [Related]
4. Identification of M2-like macrophage-related signature for predicting the prognosis, ecosystem and immunotherapy response in hepatocellular carcinoma.
Feng Q; Lu H; Wu L
PLoS One; 2023; 18(9):e0291645. PubMed ID: 37725627
[TBL] [Abstract][Full Text] [Related]
5. Machine learning developed a programmed cell death signature for predicting prognosis and immunotherapy benefits in lung adenocarcinoma.
Ding D; Wang L; Zhang Y; Shi K; Shen Y
Transl Oncol; 2023 Dec; 38():101784. PubMed ID: 37722290
[TBL] [Abstract][Full Text] [Related]
6. Machine learning constructs a T cell-related signature for predicting prognosis and drug sensitivity in ovarian cancer.
Zhang Y; Pei L
Aging (Albany NY); 2024 Feb; 16(4):3332-3349. PubMed ID: 38345575
[TBL] [Abstract][Full Text] [Related]
7. Machine learning developed an intratumor heterogeneity signature for predicting prognosis and immunotherapy benefits in skin cutaneous melanoma.
Zhang W; Wang S
Melanoma Res; 2024 Jun; 34(3):215-224. PubMed ID: 38364052
[TBL] [Abstract][Full Text] [Related]
8. Identifying the Role of Oxidative Stress-Related Genes as Prognostic Biomarkers and Predicting the Response of Immunotherapy and Chemotherapy in Ovarian Cancer.
Liu Q; Yang X; Yin Y; Zhang H; Yin F; Guo P; Zhang X; Sun C; Li S; Han Y; Yang Z
Oxid Med Cell Longev; 2022; 2022():6575534. PubMed ID: 36561981
[TBL] [Abstract][Full Text] [Related]
9. Identification of copper metabolism-related subtypes and establishment of the prognostic model in ovarian cancer.
Zhao S; Zhang X; Gao F; Chi H; Zhang J; Xia Z; Cheng C; Liu J
Front Endocrinol (Lausanne); 2023; 14():1145797. PubMed ID: 36950684
[TBL] [Abstract][Full Text] [Related]
10. A programmed cell death-related model based on machine learning for predicting prognosis and immunotherapy responses in patients with lung adenocarcinoma.
Zhang Y; Wang Y; Chen J; Xia Y; Huang Y
Front Immunol; 2023; 14():1183230. PubMed ID: 37671155
[TBL] [Abstract][Full Text] [Related]
11. Association between tumor mutation burden and immune infiltration in ovarian cancer.
Fan S; Gao X; Qin Q; Li H; Yuan Z; Zhao S
Int Immunopharmacol; 2020 Dec; 89(Pt A):107126. PubMed ID: 33189611
[TBL] [Abstract][Full Text] [Related]
12. Identification and validation of pyroptosis-related gene landscape in prognosis and immunotherapy of ovarian cancer.
Gao L; Ying F; Cai J; Peng M; Xiao M; Sun S; Zeng Y; Xiong Z; Cai L; Gao R; Wang Z
J Ovarian Res; 2023 Jan; 16(1):27. PubMed ID: 36707884
[TBL] [Abstract][Full Text] [Related]
13. Development of a necroptosis-related gene signature and the immune landscape in ovarian cancer.
Nie S; Ni N; Chen N; Gong M; Feng E; Liu J; Liu Q
J Ovarian Res; 2023 Apr; 16(1):82. PubMed ID: 37095524
[TBL] [Abstract][Full Text] [Related]
14. Identification of an Autophagy-Related Signature for Prognosis and Immunotherapy Response Prediction in Ovarian Cancer.
Ding J; Wang C; Sun Y; Guo J; Liu S; Cheng Z
Biomolecules; 2023 Feb; 13(2):. PubMed ID: 36830707
[TBL] [Abstract][Full Text] [Related]
15. Identification of immunity- and ferroptosis-related genes for predicting the prognosis of serous ovarian cancer.
Yuan X; Zhou Q; Zhang F; Zheng W; Liu H; Chen A; Tao Y
Gene; 2022 Sep; 838():146701. PubMed ID: 35777713
[TBL] [Abstract][Full Text] [Related]
16. A Novel Notch-Related Gene Signature for Prognosis and Immune Response Prediction in Ovarian Cancer.
Pi Y; Sun F; Zhang Z; Liu X; Lou G
Medicina (Kaunas); 2023 Jul; 59(7):. PubMed ID: 37512088
[No Abstract] [Full Text] [Related]
17. Identification and validation of a seven m6A-related lncRNAs signature predicting prognosis of ovarian cancer.
Song Y; Qu H
BMC Cancer; 2022 Jun; 22(1):633. PubMed ID: 35676619
[TBL] [Abstract][Full Text] [Related]
18. Identification of STEAP3-based molecular subtype and risk model in ovarian cancer.
Zhao Z; Sun C; Hou J; Yu P; Wei Y; Bai R; Yang P
J Ovarian Res; 2023 Jun; 16(1):126. PubMed ID: 37386521
[TBL] [Abstract][Full Text] [Related]
19. Ovarian cancer classification and prognosis assessment model based on prognostic target genes in key microRNA-target gene networks.
Chen X; Li Y; He J
J Gene Med; 2024 Jan; 26(1):e3575. PubMed ID: 37548130
[TBL] [Abstract][Full Text] [Related]
20. Development of a five-gene signature as a novel prognostic marker in ovarian cancer.
Wang R; Ye XH; Zhao XL; Liu JL; Zhang CY
Neoplasma; 2019 May; 66(3):343-349. PubMed ID: 30569721
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
