AUC score comparison table for all the deep learning algorithms. by Khandaker Mohammad Mohi Uddin (13124356)

Comparative overview of all DL and ML algorithms parameters in used in this study. by Khandaker Mohammad Mohi Uddin (13124356)

Hyperparameters of the LSTM Model. by Ahmed M. Elshewey (21463867)

“…Out of all the models, LSTM produced the best results. The AD-PSO-Guided WOA algorithm was used to adjust the hyperparameters for the LSTM model. …”

Prediction results of individual models. by Ahmed M. Elshewey (21463867)

“…Out of all the models, LSTM produced the best results. The AD-PSO-Guided WOA algorithm was used to adjust the hyperparameters for the LSTM model. …”

Generalized Low-Rank Plus Sparse Tensor Estimation by Fast Riemannian Optimization by Jian-Feng Cai (498405)

An optimization process of the proposed hybrid BEOSA (HBEOSA) combining both SA and FFA methods into BEOSA. by Olaide N. Oyelade (14047002)

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The Pseudo-Code of the IRBMO Algorithm. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

RMSE on the test data when fitting (logistic) quadratic models to binary data across increasing measurement error values . by Jakub Stoklosa (3315042)

Small-scale dataset comparative analysis using classification accuracy for population sizes 50 and 100. by Olaide N. Oyelade (14047002)

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Medium-scale dataset comparative analysis using classification accuracy for population sizes 50 and 100. by Olaide N. Oyelade (14047002)

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Large-scale dataset comparative analysis using classification accuracy for population sizes 50 and 100. by Olaide N. Oyelade (14047002)

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Natural language processing and machine learning algorithm to identify brain MRI reports with acute ischemic stroke by Chulho Kim (622686)

“…<div><p>Background and purpose</p><p>This project assessed performance of natural language processing (NLP) and machine learning (ML) algorithms for classification of brain MRI radiology reports into acute ischemic stroke (AIS) and non-AIS phenotypes.…”

Summary of all non-clinical data (laboratory and others) presented in the data set used by the primary studies. by Sebastião Rogério da Silva Neto (11944944)

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Models used in the works divided by the main problems. by Sebastião Rogério da Silva Neto (11944944)

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Study selection. by Sebastião Rogério da Silva Neto (11944944)

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Summary of all demographic, epidemiological and clinical data presented in data set used by the primary studies. by Sebastião Rogério da Silva Neto (11944944)

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Distribution of samples per classes. by Sebastião Rogério da Silva Neto (11944944)

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Overview of the primary studies. by Sebastião Rogério da Silva Neto (11944944)

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Metrics used to evaluate the models proposed in the literature. by Sebastião Rogério da Silva Neto (11944944)

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Attributes found in the data sets. by Sebastião Rogério da Silva Neto (11944944)

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