K-means++ clustering algorithm. by Zhen Zhao (159931)

“…Firstly, recursive feature elimination using cross validation (RFECV), maximum information coefficient (MIC), and mean decrease accuracy (MDA) methods were utilized to select population distribution feature factors. …”

K-means results. by Fei Zhang (85787)

“…<div><p>This study aims to investigate the dynamics of basketball game pace and its influence on game outcomes through a novel intra-game segmentation approach. By employing K-means clustering on possession duration, we categorized possessions from 1,141 NBA games in the 2019–2020 season into high-frequency (HFS), low-frequency (LFS), and normal-frequency segments (NFS). …”

Disrupting the PI3K complex decreases the antiviral activity of autophagy. by Ruonan Zhang (358761)

Means ± SD of isolated lens surface parameters. by Ronald A. Schachar (16674576)

State transition dynamics of reputation considering third-order information and multiple reputation values: by Hitoshi Yamamoto (738861)

Loss of MAP4K4 expression causes a decrease in the number of neutrophils. by Guihua Wang (286390)

Effects of GJE extract treatment decreased expression of NF-kB p65. by Natnicha Suttawong (22367172)

“…Brown color represents NF-kB p65 positive staining. The percentage of positive staining for NF-kB p65 (E). …”

Candidates from the RF method. The top 25 random forest candidates ranked by mean decrease in accuracy and mean decrease in Gini Index are in the first and second columns, respectively.... by Zoë Parker Cates (22184243)

“…The top 25 random forest candidates ranked by mean decrease in accuracy and mean decrease in Gini Index are in the first and second columns, respectively. …”

Mean 0-30 m sprint times for TSG, VBT, and CG groups at pre-test and post-test (with 95% CI). by Murat Tutar (22250461)

Mean 0-20 m sprint times for TSG, VBT, and CG groups at pre-test and post-test (with 95% CI). by Murat Tutar (22250461)

Mean 0-10 m sprint times for TSG, VBT, and CG groups at pre-test and post-test (with 95% CI). by Murat Tutar (22250461)

SH3KBP1 promotes K63-linked polyubiquitination of RIG-I by recruiting TRIM25. by Jiaoyang Li (2862269)

Supplementary file 1_Identifying early blood glucose trajectories in sepsis linked to distinct long-term outcomes: a K-means clustering study with external validation.docx by Huan Ma (713125)

“…Distinct clusters were demarcated using K-means clustering based on the BG trajectory within the first 48 hours after ICU admission, while the optimal number of clusters was determined by a consensus of quantitative metrics and the elbow plot. …”

IRE1 depletion decreases heterochromatin, DNA, and H3K9me3 methylation, and UHRF1. by Iratxe Zuazo-Gaztelu (21071939)

IRE1 depletion decreases heterochromatin, DNA and H3K9me3 methylation, and UHRF1. by Iratxe Zuazo-Gaztelu (21071939)

MAP3K1, MAPK11, and PPP2R1A knockdown decreased ECM internalisation. by Montserrat Llanses Martinez (17797522)

Image 1_Relationship between triglyceride glucose-body mass index baselines and variation with future cardiovascular diseases risk in the middle-aged and elderly individuals.jpeg by Junpeng Qiao (11726521)

“…The change of TyG-BMI was categorized using K-means clustering and baseline TyG-BMI was grouped based on quartiles. …”

Image 2_Relationship between triglyceride glucose-body mass index baselines and variation with future cardiovascular diseases risk in the middle-aged and elderly individuals.jpeg by Junpeng Qiao (11726521)

“…The change of TyG-BMI was categorized using K-means clustering and baseline TyG-BMI was grouped based on quartiles. …”

Table 1_Relationship between triglyceride glucose-body mass index baselines and variation with future cardiovascular diseases risk in the middle-aged and elderly individuals.docx by Junpeng Qiao (11726521)

“…The change of TyG-BMI was categorized using K-means clustering and baseline TyG-BMI was grouped based on quartiles. …”

Mean responses to the Oxford Utilitarianism Scale and its subscales. by Aistė Ambrasė (22505574)

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