Descriptive statistical analysis of data. by Xiangjuan Liu (618000)

“…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. Finally, the Beluga Whale Optimization (BWO)-tuned STL-PCA-BWO-BiLSTM hybrid model delivered optimal performance on test sets (RMSE = 0.22, MAE = 0.16, MAPE = 0.99%, ), exhibiting 40.7% higher accuracy than unoptimized BiLSTM (MAE = 0.27). …”

The MAE value of the model under raw data. by Xiangjuan Liu (618000)

“…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. Finally, the Beluga Whale Optimization (BWO)-tuned STL-PCA-BWO-BiLSTM hybrid model delivered optimal performance on test sets (RMSE = 0.22, MAE = 0.16, MAPE = 0.99%, ), exhibiting 40.7% higher accuracy than unoptimized BiLSTM (MAE = 0.27). …”

Three error values under raw data. by Xiangjuan Liu (618000)

“…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. Finally, the Beluga Whale Optimization (BWO)-tuned STL-PCA-BWO-BiLSTM hybrid model delivered optimal performance on test sets (RMSE = 0.22, MAE = 0.16, MAPE = 0.99%, ), exhibiting 40.7% higher accuracy than unoptimized BiLSTM (MAE = 0.27). …”

Decomposition of time scries plot. by Xiangjuan Liu (618000)

“…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. Finally, the Beluga Whale Optimization (BWO)-tuned STL-PCA-BWO-BiLSTM hybrid model delivered optimal performance on test sets (RMSE = 0.22, MAE = 0.16, MAPE = 0.99%, ), exhibiting 40.7% higher accuracy than unoptimized BiLSTM (MAE = 0.27). …”

BMI groups by SES. by Krystal Hunter (6820052)

“…This relationship was not found in higher economic status women. Our study had two significant findings. …”

BMISES_Data_Part2. by Krystal Hunter (6820052)

“…This relationship was not found in higher economic status women. Our study had two significant findings. …”

Logistic regression for LSES population. by Krystal Hunter (6820052)

“…This relationship was not found in higher economic status women. Our study had two significant findings. …”

Logistic regression for HSES population. by Krystal Hunter (6820052)

“…This relationship was not found in higher economic status women. Our study had two significant findings. …”

Logistic regression for overall population. by Krystal Hunter (6820052)

“…This relationship was not found in higher economic status women. Our study had two significant findings. …”

BMISES_Data_Part1. by Krystal Hunter (6820052)

“…This relationship was not found in higher economic status women. Our study had two significant findings. …”

Baseline characteristics of HSES/LSES population. by Krystal Hunter (6820052)

“…This relationship was not found in higher economic status women. Our study had two significant findings. …”

Baseline characteristics of overall population. by Krystal Hunter (6820052)

“…This relationship was not found in higher economic status women. Our study had two significant findings. …”

Diagram of study population. by Krystal Hunter (6820052)

“…This relationship was not found in higher economic status women. Our study had two significant findings. …”

Malaria prevalence over the years is presented by age (Fig 3A), sex (Fig 3B), history of fever (Fig 3C), geographical zones (Fig 3D), ITN use (Fig 3E), and elevation (Fig 3F). by Frank Chacky (3446654)

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Crude and adjusted odds ratios of malaria prevalence in school children using multilevel mixed-effect logistic regression model in mainland Tanzania, 2015–2023. by Frank Chacky (3446654)

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Socio-demographic characteristics of the survey participants 2015–2023. by Frank Chacky (3446654)

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A map of Tanzania indicating surveyed schools along with regional and council boundaries was created. by Frank Chacky (3446654)

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Malaria infection prevalence across different age groups and survey years is presented. by Frank Chacky (3446654)

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S1 Fig - by Frank Chacky (3446654)

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Pneumococcal (black bars) and influenza (white bars) vaccine coverage in patients living with comorbidities (A), and immunosuppressive conditions (B) according to age of 65 years,... by Benjamin Wyplosz (22032756)

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