Major hyperparameters of RF-MLPR. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Results of RF algorithm screening factors. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Schematic diagram of the basic principles of SVR. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Connectivity (frontal, axial, and sagittal planes) and color maps of between-group analysis of the tDCS intervention. by Rael Lopes Alves (7877942)

“…<p>The colored edge represents connections with significant differences. (A) Maps shows decreased connectivity between left ACC and right INS in the HB-a-tDCS on DLPFC group in the delta frequency band which present large effect size (Cohen’s d = 1.69). …”

Comparison of mapping efficiency with varying DNA input amounts. by Amy Longtin (21409957)

Comparison of probe capture with varying protocol modifications. by Amy Longtin (21409957)

Flowchart depicting the selection of the study population. by Xiaoling Zhong (181270)

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Signal strength of reports of finasteride administration at the PT level (age < 18). by Xiaoling Zhong (181270)

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Signal strength of reports of finasteride administration at the preferred term level in the FAERS database. by Xiaoling Zhong (181270)

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Time to onset of AEs in male and female patients receiving finasteride therapy. by Xiaoling Zhong (181270)

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Signal strength of reports of finasteride administration at the SOC level. by Xiaoling Zhong (181270)

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Signal strength of reports of finasteride administration at the SOC level by Xiaoling Zhong (181270)

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Signal strength of reports of finasteride administration in female at the PT level. by Xiaoling Zhong (181270)

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Signal strength of reports of finasteride administration in male at the PT level. by Xiaoling Zhong (181270)

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Signal strength of reports of finasteride administration at the PT level (age = 18-65). by Xiaoling Zhong (181270)

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Signal strength of reports of finasteride administration at the PT level (age>=65). by Xiaoling Zhong (181270)

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Clinical characteristics of reports with finasteride as the primary suspected drug from the FAERS database. by Xiaoling Zhong (181270)

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Sex-differentiated risk signal volcano plot for finasteride. by Xiaoling Zhong (181270)

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Number of adverse reaction case reports of finasteride administration at the PT level. by Xiaoling Zhong (181270)

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Apoptosis induced by bortezomib/venetoclax was stronger in sLCL expressing BHRF-1, EBNA-3C, LMP-1 and Noxa. by Kam Pui Tam (19746865)