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• Research PaperVolume 15, Issue 1pp 193-212

  A two-gene random forest model to diagnose osteoarthritis based on RNA-binding protein-related genes in knee cartilage tissue

  Relevance score: 0.00

  Wenhua Yin, Ying Lei, Xuan Yang, Jiawei Zou

  Keywords: osteoarthritis, RNA-binding protein, diagnosis, machine learning, random forest

  Published in Aging on January 5, 2023

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• Research PaperVolume 16, Issue 14pp 11248-11274

  A stemness-based signature with inspiring indications in discriminating the prognosis, immune response, and somatic mutation of endometrial cancer patients revealed by machine learning

  Relevance score: 0.00

  Xuecheng Pang, Yu Wang, Qiang Zhang, Sumin Qian

  Keywords: endometrial cancer, random forest, stemness subtype, mRANsi, prognostic model

  Published in Aging on July 30, 2024

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• Research PaperVolume 15, Issue 5pp 1475-1495

  Identification MNS1, FRZB, OGN, LUM, SERP1NA3 and FCN3 as the potential immune-related key genes involved in ischaemic cardiomyopathy by random forest and nomogram

  Relevance score: 0.00

  Peng-Fei Zheng, Fen Liu, Zhao-Fen Zheng, Hong-Wei Pan, Zheng-Yu Liu

  Keywords: ischaemic cardiomyopathy, random forest, immune cell infiltrates, bioinformatics analysis, immune-related genes

  Published in Aging on February 27, 2023

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• Research PaperVolume 13, Issue 21pp 24219-24235

  Construction and external validation of a 5-gene random forest model to diagnose non-obstructive azoospermia based on the single-cell RNA sequencing of testicular tissue

  Relevance score: 0.00

  Ranran Zhou, Xianyuan Lv, Tianle Chen, Qi Chen, Hu Tian, Cheng Yang, Wenbin Guo, Cundong Liu

  Keywords: non-obstructive azoospermia, diagnosis, scRNA-seq, random forest, machine learning

  Published in Aging on November 4, 2021

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• Research PaperVolume 12, Issue 24pp 26221-26235

  Construction and analysis of a joint diagnosis model of random forest and artificial neural network for heart failure

  Relevance score: 0.00

  Yuqing Tian, Jiefu Yang, Ming Lan, Tong Zou

  Keywords: difference analysis, heart failure, artificial neural network, random forest

  Published in Aging on December 26, 2020

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• Research PaperVolume 16, Issue 4pp 3420-3530

  Insights into serum metabolic biomarkers for early detection of incident diabetic kidney disease in Chinese patients with type 2 diabetes by random forest

  Relevance score: 0.00

  Jian-Jun Jiang, Tung-Ting Sham, Xiu-Fen Gu, Chi-On Chan, Nai-Ping Dong, Wei-Han Lim, Gao-Feng Song, Shun-Min Li, Daniel Kam-Wah Mok, Na Ge

  Keywords: diabetic kidney disease, biomarkers, untargeted metabolomics, random forest

  Published in Aging on February 12, 2024

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• Research PaperVolume 15, Issue 24pp 15657-15675

  Placenta autophagy is closely associated with preeclampsia

  Relevance score: 0.00

  Chaomei Li, Wei Liu, Qunxiu Lao, Haiying Lu, Yingting Zhao

  Keywords: preeclampsia (PE), autophagy, random forest, nomogram, immune

  Published in Aging on December 19, 2022

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• Research PaperVolume 12, Issue 20pp 20471-20482

  Development of a susceptibility gene based novel predictive model for the diagnosis of ulcerative colitis using random forest and artificial neural network

  Relevance score: 0.00

  Hanyang Li, Lijie Lai, Jun Shen

  Keywords: ulcerative colitis, predictive model, susceptibility genes, random forest, artificial neural network

  Published in Aging on October 24, 2020

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• Research PaperVolume 12, Issue 22pp 23351-23378

  Cognitive reserve and network efficiency as compensatory mechanisms of the effect of aging on phonemic fluency

  Relevance score: 0.00

  Lissett Gonzalez-Burgos, José Barroso, Daniel Ferreira

  Keywords: compensation, phonemic fluency, aging, random forest, graph theory

  Published in Aging on November 17, 2020

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• Research PaperVolume 12, Issue 20pp 19938-19944

  An improved multivariate model that distinguishes COVID-19 from seasonal flu and other respiratory diseases

  Relevance score: 0.00

  Xing Guo, Yanrong Li, Hua Li, Xueqin Li, Xu Chang, Xuemei Bai, Zhanghong Song, Junfeng Li, Kefeng Li

  Keywords: COVID-19, multi-feature, influenza, random forest, diagnostic model

  Published in Aging on October 21, 2020

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• Research PaperVolume 11, Issue 12pp 4090-4106

  Cognitive compensatory mechanisms in normal aging: a study on verbal fluency and the contribution of other cognitive functions

  Relevance score: 0.00

  Lissett Gonzalez-Burgos, Juan Andrés Hernández-Cabrera, Eric Westman, José Barroso, Daniel Ferreira

  Keywords: verbal fluency, aging, differentiation, compensation, random forest

  Published in Aging on June 22, 2019

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• Research PaperVolume 16, Issue 9pp 7774-7798

  The identification of a N⁶-methyladenosin-modifed immune pattern to predict immunotherapy response and survival in urothelial carcinoma

  Relevance score: 0.00

  Xudong Mao, Xianjiong Chen, Zhehao Xu, Lifeng Ding, Wenqin Luo, Yudong Lin, Ruyue Wang, Liqun Xia, Mingchao Wang, Gonghui Li

  Keywords: urothelial carcinoma, immune genes, prognosis, immunotherapeutic response, N⁶-methyladenosin, Cox proportional hazard model, random survival forest variable hunting, database analysis

  Published in Aging on May 1, 2024

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• Research PaperVolume 12, Issue 20pp 20512-20522

  RWR-algorithm-based dissection of microRNA-506-3p and microRNA-140-5p as radiosensitive biomarkers in colorectal cancer

  Relevance score: 0.00

  Fei Liao, Xin Chen, Pailan Peng, Weiguo Dong

  Keywords: colorectal cancer, radiosensitivity, microRNA, random walk with restart

  Published in Aging on October 8, 2020

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