Proposed model specificity and DSC outcomes. by Subathra Gunasekaran (19492680)

“…Next, we employ batch normalization to smooth and enhance the collected data, followed by feature extraction using the AlexNet model. …”

Bi-directional LSTM Model performance. by Muhammad Usman Tariq (11022141)

“…Analytic approaches, both predictive and retrospective in nature, were used to interpret the data. Our primary objective was to determine the most effective model for predicting COVID-19 cases in the United Arab Emirates (UAE) and Malaysia. …”

Prediction results of different models. by Qinghua Li (398885)

“…In the hybrid model of this paper, the choice was made to use the Densenet architecture of CNN models with LightGBM as the primary model. …”

Data_Sheet_1_Phase-wise evaluation and optimization of non-pharmaceutical interventions to contain the COVID-19 pandemic in the U.S..pdf by Xiao Zhou (122661)

S1 Data - by Gaosha Li (20570760)

“…A combination of four machine learning algorithms (XGBoost、Logistic Regression、Random Forest、AdaBoost) was employed to predict NPM recurrence, and the model with the highest Area Under the Curve (AUC) in the test set was selected as the best model. …”

DataSheet_1_Stronger wind, smaller tree: Testing tree growth plasticity through a modeling approach.docx by Haoyu Wang (429641)

Supporting data for “The role of forest composition heterogeneity on temperate ecosystem carbon dynamic under climate change" by Ziyu Lin (9151064)

Consort diagram for the study. by Nicola Lazzarini (3528197)

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Performance confidence intervals. by Nicola Lazzarini (3528197)

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Baseline characteristics of patients in the study cohort. by Nicola Lazzarini (3528197)

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Input features. by Nicola Lazzarini (3528197)

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Most important predictive features. by Nicola Lazzarini (3528197)

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Age feature importance. by Nicola Lazzarini (3528197)

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Machine learning vs. clinicians. by Nicola Lazzarini (3528197)

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ROC curves. by Nicola Lazzarini (3528197)

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PR curves. by Nicola Lazzarini (3528197)

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Overview of the cohort definition process. by Nicola Lazzarini (3528197)

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Overall Framework of the PSO-KM Model. by Hongwei Yue (574068)

Overall Framework of the PSO-KM Model. by Hongwei Yue (574068)

Comparison of the four models. by Gaosha Li (20570760)

“…A combination of four machine learning algorithms (XGBoost、Logistic Regression、Random Forest、AdaBoost) was employed to predict NPM recurrence, and the model with the highest Area Under the Curve (AUC) in the test set was selected as the best model. …”