N-acetilcysteine prevents the <i>A</i>. <i>simplex</i> CE-induced TEER decrease. by Noelia Carballeda-Sangiao (2889611)

JNJ26993135 + BML-111 decreases permeability and enhances ZO-1 and claudin-1 induced by PAF but does not change TEER. by Kameljit K. Kalsi (16496511)

Beeswarm plot, ranked by mean absolute SHAP value generated by optimized Random Forest model. by Shimels Derso Kebede (16813901)

Subjects:

BA attenuated the decrease in the expression of ZO-1 and Occludin induced by LPS in Caco2 cells. by Luqiong Liu (11537092)

GXM decreases the trans-endothelial electrical resistance (TEER) and transmigration of <i>C</i>. <i>neoformans</i> through HBECs in a blood brain barrier (BBB) model. by Hiu Ham Lee (15374677)

Importance of Predictors Based on SHAP Value. by Mengdie Xue (21608366)

Y-27632 collaborated with BA to attenuate the increase in the integrity and decrease in the permeability of epithelial barrier injury induced by LPS in Caco2 monolayers. by Luqiong Liu (11537092)

“…The values are expressed as the means ± SDs and were analyzed according to the variance of the factorial design. **, *** and ****denote <i>p</i> < 0.01, < 0.001 and < 0.0001, respectively; ns  =  not significant.…”

Y-27632 synergized with BA to alleviate the decrease in the expression of and abnormal localization of ZO-1 and Occludin in LPS-induced Caco2 cells. by Luqiong Liu (11537092)

Feature Impact Summary Based on SHAP Values. by Zhipeng Wei (1418458)

Feature Impact Summary Based on SHAP Values. by Zhipeng Wei (1418458)

SHAP interpretation of the optimal machine learning model. by Wentao Yang (205781)

Subjects:

SHAP interpretation. by Nguyen Minh Khiem (13883817)

Feature importance ranking based on SHAP values. by Feng Wang (44414)

SHAP. by Sasja Maria Pedersen (11880264)

Subjects:

SHAP of stacking. by Wenguang Li (6528113)

Table 2_Significant adverse prognostic events in patients with urosepsis: a machine learning based model development and validation study.docx by Yiqu Wei (22011386)

Image 4_Significant adverse prognostic events in patients with urosepsis: a machine learning based model development and validation study.tif by Yiqu Wei (22011386)

Image 1_Significant adverse prognostic events in patients with urosepsis: a machine learning based model development and validation study.tif by Yiqu Wei (22011386)

Image 3_Significant adverse prognostic events in patients with urosepsis: a machine learning based model development and validation study.tif by Yiqu Wei (22011386)

Table 1_Significant adverse prognostic events in patients with urosepsis: a machine learning based model development and validation study.docx by Yiqu Wei (22011386)