198 related articles for article (PubMed ID: 29328363)
1. Support vector machine classifier for prediction of the metastasis of colorectal cancer.
Zhi J; Sun J; Wang Z; Ding W
Int J Mol Med; 2018 Mar; 41(3):1419-1426. PubMed ID: 29328363
[TBL] [Abstract][Full Text] [Related]
2. A support vector machine classifier for the prediction of osteosarcoma metastasis with high accuracy.
He Y; Ma J; Ye X
Int J Mol Med; 2017 Nov; 40(5):1357-1364. PubMed ID: 28901446
[TBL] [Abstract][Full Text] [Related]
3. Feature genes in metastatic breast cancer identified by MetaDE and SVM classifier methods.
Tuo Y; An N; Zhang M
Mol Med Rep; 2018 Mar; 17(3):4281-4290. PubMed ID: 29328377
[TBL] [Abstract][Full Text] [Related]
4. Construction of a 26‑feature gene support vector machine classifier for smoking and non‑smoking lung adenocarcinoma sample classification.
Yang L; Sun L; Wang W; Xu H; Li Y; Zhao JY; Liu DZ; Wang F; Zhang LY
Mol Med Rep; 2018 Feb; 17(2):3005-3013. PubMed ID: 29257283
[TBL] [Abstract][Full Text] [Related]
5. A multigene support vector machine predictor for metastasis of cutaneous melanoma.
Wei D
Mol Med Rep; 2018 Feb; 17(2):2907-2914. PubMed ID: 29257259
[TBL] [Abstract][Full Text] [Related]
6. Establishment of a SVM classifier to predict recurrence of ovarian cancer.
Zhou J; Li L; Wang L; Li X; Xing H; Cheng L
Mol Med Rep; 2018 Oct; 18(4):3589-3598. PubMed ID: 30106117
[TBL] [Abstract][Full Text] [Related]
7. Identification of potential biomarkers with colorectal cancer based on bioinformatics analysis and machine learning.
Hammad A; Elshaer M; Tang X
Math Biosci Eng; 2021 Oct; 18(6):8997-9015. PubMed ID: 34814332
[TBL] [Abstract][Full Text] [Related]
8. A 80-gene set potentially predicts the relapse in laryngeal carcinoma optimized by support vector machine.
Yang B; Guo Q; Wang F; Cai K; Bao X; Chu J
Cancer Biomark; 2017; 19(1):65-73. PubMed ID: 28269752
[TBL] [Abstract][Full Text] [Related]
9. A 16-gene expression signature to distinguish stage I from stage II lung squamous carcinoma.
Wang R; Cai Y; Zhang B; Wu Z
Int J Mol Med; 2018 Mar; 41(3):1377-1384. PubMed ID: 29286069
[TBL] [Abstract][Full Text] [Related]
10. Identifying the key genes and microRNAs in colorectal cancer liver metastasis by bioinformatics analysis and in vitro experiments.
Zhang T; Guo J; Gu J; Wang Z; Wang G; Li H; Wang J
Oncol Rep; 2019 Jan; 41(1):279-291. PubMed ID: 30542696
[TBL] [Abstract][Full Text] [Related]
11. Delineating the underlying molecular mechanisms and key genes involved in metastasis of colorectal cancer via bioinformatics analysis.
Qi C; Chen Y; Zhou Y; Huang X; Li G; Zeng J; Ruan Z; Xie X; Zhang J
Oncol Rep; 2018 May; 39(5):2297-2305. PubMed ID: 29517105
[TBL] [Abstract][Full Text] [Related]
12. Construction of a 5-feature gene model by support vector machine for classifying osteoporosis samples.
Hu M; Zou L; Lu J; Yang Z; Chen Y; Xu Y; Sun C
Bioengineered; 2021 Dec; 12(1):6821-6830. PubMed ID: 34622712
[TBL] [Abstract][Full Text] [Related]
13. Signature microRNAs and long noncoding RNAs in laryngeal cancer recurrence identified using a competing endogenous RNA network.
Tang Z; Wei G; Zhang L; Xu Z
Mol Med Rep; 2019 Jun; 19(6):4806-4818. PubMed ID: 31059106
[TBL] [Abstract][Full Text] [Related]
14. The identification of a common different gene expression signature in patients with colorectal cancer.
Zhao ZW; Fan XX; Yang LL; Song JJ; Fang SJ; Tu JF; Chen MJ; Zheng LY; Wu FZ; Zhang DK; Ying XH; Ji JS
Math Biosci Eng; 2019 Apr; 16(4):2942-2958. PubMed ID: 31137244
[TBL] [Abstract][Full Text] [Related]
15. A 21‑gene Support Vector Machine classifier and a 10‑gene risk score system constructed for patients with gastric cancer.
Jiang H; Gu J; Du J; Qi X; Qian C; Fei B
Mol Med Rep; 2020 Jan; 21(1):347-359. PubMed ID: 31939629
[TBL] [Abstract][Full Text] [Related]
16. SVM-T-RFE: a novel gene selection algorithm for identifying metastasis-related genes in colorectal cancer using gene expression profiles.
Li X; Peng S; Chen J; Lü B; Zhang H; Lai M
Biochem Biophys Res Commun; 2012 Mar; 419(2):148-53. PubMed ID: 22306013
[TBL] [Abstract][Full Text] [Related]
17. Identification of biomarkers associated with diagnosis and prognosis of colorectal cancer patients based on integrated bioinformatics analysis.
Chen L; Lu D; Sun K; Xu Y; Hu P; Li X; Xu F
Gene; 2019 Apr; 692():119-125. PubMed ID: 30654001
[TBL] [Abstract][Full Text] [Related]
18. Identification of hub genes and pathways in lung metastatic colorectal cancer.
Dai W; Guo C; Wang Y; Li Y; Xie R; Wu J; Yao B; Xie D; He L; Li Y; Huang H; Wang Y; Liu S
BMC Cancer; 2023 Apr; 23(1):323. PubMed ID: 37024866
[TBL] [Abstract][Full Text] [Related]
19. Screening key genes and signaling pathways in colorectal cancer by integrated bioinformatics analysis.
Yu C; Chen F; Jiang J; Zhang H; Zhou M
Mol Med Rep; 2019 Aug; 20(2):1259-1269. PubMed ID: 31173250
[TBL] [Abstract][Full Text] [Related]
20. A six‑gene support vector machine classifier contributes to the diagnosis of pediatric septic shock.
Long G; Yang C
Mol Med Rep; 2020 Mar; 21(3):1561-1571. PubMed ID: 32016447
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
