120 related articles for article (PubMed ID: 38215553)
1. Identification of diagnostic signatures for ischemic stroke by machine learning algorithm.
Li Q; Tian Y; Niu J; Guo E; Lu Y; Dang C; Feng L; Li L; Wang L
J Stroke Cerebrovasc Dis; 2024 Mar; 33(3):107564. PubMed ID: 38215553
[TBL] [Abstract][Full Text] [Related]
2. Identification of diagnostic signatures associated with immune infiltration in Alzheimer's disease by integrating bioinformatic analysis and machine-learning strategies.
Tian Y; Lu Y; Cao Y; Dang C; Wang N; Tian K; Luo Q; Guo E; Luo S; Wang L; Li Q
Front Aging Neurosci; 2022; 14():919614. PubMed ID: 35966794
[TBL] [Abstract][Full Text] [Related]
3. Identification of immune-related key genes in the peripheral blood of ischaemic stroke patients using a weighted gene coexpression network analysis and machine learning.
Zheng PF; Chen LZ; Liu P; Pan HW; Fan WJ; Liu ZY
J Transl Med; 2022 Aug; 20(1):361. PubMed ID: 35962388
[TBL] [Abstract][Full Text] [Related]
4. Development of a novel immune infiltration-related diagnostic model for Alzheimer's disease using bioinformatic strategies.
Zhuang X; Zhang G; Bao M; Jiang G; Wang H; Li S; Wang Z; Sun X
Front Immunol; 2023; 14():1147501. PubMed ID: 37545529
[TBL] [Abstract][Full Text] [Related]
5. Identification of anoikis-related genes classification patterns and immune infiltration characterization in ischemic stroke based on machine learning.
Qin X; Yi S; Rong J; Lu H; Ji B; Zhang W; Ding R; Wu L; Chen Z
Front Aging Neurosci; 2023; 15():1142163. PubMed ID: 37032832
[TBL] [Abstract][Full Text] [Related]
6. Discovery and validation of molecular patterns and immune characteristics in the peripheral blood of ischemic stroke patients.
Cong L; He Y; Wu Y; Li Z; Ding S; Liang W; Xiao X; Zhang H; Wang L
PeerJ; 2024; 12():e17208. PubMed ID: 38650649
[TBL] [Abstract][Full Text] [Related]
7. Identification of diagnostic genes for both Alzheimer's disease and Metabolic syndrome by the machine learning algorithm.
Li J; Zhang Y; Lu T; Liang R; Wu Z; Liu M; Qin L; Chen H; Yan X; Deng S; Zheng J; Liu Q
Front Immunol; 2022; 13():1037318. PubMed ID: 36405716
[TBL] [Abstract][Full Text] [Related]
8. Identification of Diagnostic Signatures and Immune Cell Infiltration Characteristics in Rheumatoid Arthritis by Integrating Bioinformatic Analysis and Machine-Learning Strategies.
Yu R; Zhang J; Zhuo Y; Hong X; Ye J; Tang S; Zhang Y
Front Immunol; 2021; 12():724934. PubMed ID: 34691030
[TBL] [Abstract][Full Text] [Related]
9. Bioinformatics identification of potential biomarkers and therapeutic targets for ischemic stroke and vascular dementia.
Zhang D; Jia N; Hu Z; Keqing Z; Chenxi S; Chunying S; Chen C; Chen W; Hu Y; Ruan Z
Exp Gerontol; 2024 Mar; 187():112374. PubMed ID: 38320734
[TBL] [Abstract][Full Text] [Related]
10. Predicting diagnostic gene expression profiles associated with immune infiltration in patients with lupus nephritis.
Wang L; Yang Z; Yu H; Lin W; Wu R; Yang H; Yang K
Front Immunol; 2022; 13():839197. PubMed ID: 36532018
[TBL] [Abstract][Full Text] [Related]
11. Unfolded protein response pathways in stroke patients: a comprehensive landscape assessed through machine learning algorithms and experimental verification.
Yu H; Ji X; Ouyang Y
J Transl Med; 2023 Oct; 21(1):759. PubMed ID: 37891634
[TBL] [Abstract][Full Text] [Related]
12. [Screen of key characteristic genes of nasopharyngeal carcinoma (NPC) base on machine learning and analysis of their correlation with immune cells].
Zhang H; Ma J; An S; Xu L; Lu J; Jiang C
Xi Bao Yu Fen Zi Mian Yi Xue Za Zhi; 2023 Number; 39(11):988-995. PubMed ID: 37980550
[TBL] [Abstract][Full Text] [Related]
13. Comparison of ischemic stroke diagnosis models based on machine learning.
Yang WX; Wang FF; Pan YY; Xie JQ; Lu MH; You CG
Front Neurol; 2022; 13():1014346. PubMed ID: 36545400
[TBL] [Abstract][Full Text] [Related]
14. Machine-Learning Algorithm-Based Prediction of Diagnostic Gene Biomarkers Related to Immune Infiltration in Patients With Chronic Obstructive Pulmonary Disease.
Zhang Y; Xia R; Lv M; Li Z; Jin L; Chen X; Han Y; Shi C; Jiang Y; Jin S
Front Immunol; 2022; 13():740513. PubMed ID: 35350787
[TBL] [Abstract][Full Text] [Related]
15. Identification of TYR, TYRP1, DCT and LARP7 as related biomarkers and immune infiltration characteristics of vitiligo via comprehensive strategies.
Zhang J; Yu R; Guo X; Zou Y; Chen S; Zhou K; Chen Y; Li Y; Gao S; Wu Y
Bioengineered; 2021 Dec; 12(1):2214-2227. PubMed ID: 34107850
[TBL] [Abstract][Full Text] [Related]
16. Elucidating the multifaceted roles of GPR146 in non-specific orbital inflammation: a concerted analytical approach through the prisms of bioinformatics and machine learning.
Wu Z; Li L; Xu T; Hu Y; Peng X; Zhang Z; Yao X; Peng Q
Front Med (Lausanne); 2024; 11():1309510. PubMed ID: 38903815
[TBL] [Abstract][Full Text] [Related]
17. Bioinformatics analysis of the immune cell infiltration characteristics and correlation with crucial diagnostic markers in pulmonary arterial hypertension.
Lian G; You J; Lin W; Gao G; Xu C; Wang H; Luo L
BMC Pulm Med; 2023 Aug; 23(1):300. PubMed ID: 37582718
[TBL] [Abstract][Full Text] [Related]
18. Identification of hub genes and their correlation with immune infiltration in coronary artery disease through bioinformatics and machine learning methods.
Huang KK; Zheng HL; Li S; Zeng ZY
J Thorac Dis; 2022 Jul; 14(7):2621-2634. PubMed ID: 35928610
[TBL] [Abstract][Full Text] [Related]
19. Machine learning to identify immune-related biomarkers of rheumatoid arthritis based on WGCNA network.
Chen Y; Liao R; Yao Y; Wang Q; Fu L
Clin Rheumatol; 2022 Apr; 41(4):1057-1068. PubMed ID: 34767108
[TBL] [Abstract][Full Text] [Related]
20. Identification of hypoxia-related genes and exploration of their relationship with immune cells in ischemic stroke.
Yang K; Zhang Z; Liu X; Wang T; Jia Z; Li X; Liu W
Sci Rep; 2023 Jun; 13(1):10570. PubMed ID: 37386280
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]