172 related articles for article (PubMed ID: 37851341)
1. 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]
2. Machine learning developed a CD8
Chen R; Zheng Y; Fei C; Ye J; Fei H
Sci Rep; 2024 Mar; 14(1):5794. PubMed ID: 38461331
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. Machine learning developed a fibroblast-related signature for predicting clinical outcome and drug sensitivity in ovarian cancer.
Fu W; Feng Q; Tao R
Medicine (Baltimore); 2024 Apr; 103(16):e37783. PubMed ID: 38640321
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. Machine learning-based cell death signature for predicting the prognosis and immunotherapy benefit in stomach adenocarcinoma.
Li F; Feng Q; Tao R
Medicine (Baltimore); 2024 Mar; 103(10):e37314. PubMed ID: 38457593
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. 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]
9. Assessing of programmed cell death gene signature for predicting ovarian cancer prognosis and treatment response.
Lian X; Liu B; Wang C; Wang S; Zhuang Y; Li X
Front Endocrinol (Lausanne); 2023; 14():1182776. PubMed ID: 37342266
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. 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]
12. Comprehensive analysis of the interaction of antigen presentation during anti-tumour immunity and establishment of AIDPS systems in ovarian cancer.
Sun W; Xu P; Gao K; Lian W; Sun X
J Cell Mol Med; 2024 Apr; 28(8):e18309. PubMed ID: 38613345
[TBL] [Abstract][Full Text] [Related]
13. TEAD4 functions as a prognostic biomarker and triggers EMT via PI3K/AKT pathway in bladder cancer.
Chi M; Liu J; Mei C; Shi Y; Liu N; Jiang X; Liu C; Xue N; Hong H; Xie J; Sun X; Yin B; Meng X; Wang B
J Exp Clin Cancer Res; 2022 May; 41(1):175. PubMed ID: 35581606
[TBL] [Abstract][Full Text] [Related]
14. Bioinformatic profiling identifies a platinum-resistant-related risk signature for ovarian cancer.
Wu C; He L; Wei Q; Li Q; Jiang L; Zhao L; Wang C; Li J; Wei M
Cancer Med; 2020 Feb; 9(3):1242-1253. PubMed ID: 31856408
[TBL] [Abstract][Full Text] [Related]
15. A risk prediction model of gene signatures in ovarian cancer through bagging of GA-XGBoost models.
Hsiao YW; Tao CL; Chuang EY; Lu TP
J Adv Res; 2021 May; 30():113-122. PubMed ID: 34026291
[TBL] [Abstract][Full Text] [Related]
16. Long noncoding RNA-JPX predicts the poor prognosis of ovarian cancer patients and promotes tumor cell proliferation, invasion and migration by the PI3K/Akt/mTOR signaling pathway.
Li J; Feng L; Tian C; Tang YL; Tang Y; Hu FQ
Eur Rev Med Pharmacol Sci; 2018 Dec; 22(23):8135-8144. PubMed ID: 30556851
[TBL] [Abstract][Full Text] [Related]
17. UBE2S promotes the development of ovarian cancer by promoting PI3K/AKT/mTOR signaling pathway to regulate cell cycle and apoptosis.
Zhang M; Liu Y; Yin Y; Sun Z; Wang Y; Zhang Z; Li F; Chen X
Mol Med; 2022 Jun; 28(1):62. PubMed ID: 35658829
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. Lysine demethylase 2A promotes the progression of ovarian cancer by regulating the PI3K pathway and reversing epithelial‑mesenchymal transition.
Lu DH; Yang J; Gao LK; Min J; Tang JM; Hu M; Li Y; Li ST; Chen J; Hong L
Oncol Rep; 2019 Feb; 41(2):917-927. PubMed ID: 30483796
[TBL] [Abstract][Full Text] [Related]
20. Prognosis and tumor immune microenvironment of patients with gastric cancer by a novel senescence-related signature.
Zhang G; Dong K; Liu J; Zhou W
Medicine (Baltimore); 2022 Oct; 101(40):e30927. PubMed ID: 36221394
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
