Table 2 AI and ML algorithms and platforms used in reviewed studies

Parham, G.P. et al.⁶⁵

DL [CNN]

Camera

Movahedi Nia, Z. et al.⁶⁶

DL & Topic Modeling [RoBERTa]

Twitter

Maturana, C.R. et al.⁶⁷

DL [YOLOv5x, Faster R-CNN, SSD, RetinaNet]

Microscope

Kabukye, J.K. et al.⁶⁸

DL [Unspecified]

Telemedicine System

Turon, G. et al.⁶⁹

SL [Tree-based Machine Learning and AutoML]

Fredriksson, A. et al.⁷⁰

SL [Multivariate logistic regression, Logistic model using LASSO (Least Absolute Shrinkage and Selection Operator) regularization, Random Forest, Artificial neural network]

Data collection

Ogbuokiri, B. et al.⁷¹

SL [KNN, SVM, Logistic regression, VADER (Valence Aware Dictionary for Sentiment Reasoning), Decision tree]

Twitter

Dacal, E. et al.⁷²

DL [FasterRCNN-ResNet50, SSD-MobileNet]

Microscope

Gbashi, S. et al.⁷³

Computational linguistics models [TextBlob, Valence Aware Dictionary, Sentiment Reasoner, World2Vec combined with a bidirectional long short-term memory neural network]

Google News, Twitter

Bruzelius, E. et al.⁷⁴

DL [TensorBox]

Mapping of images

Schaible, B. J. et al.¹⁷

Topic modeling [Latent Dirichlet Allocation]

Twitter

Kraemer, M.U.G. et al.⁷⁵

SL [Logistic model, Boosted regression tree]

Data collection and mobility tracking

Odlum, M. & Yoon, S. ¹⁸

Natural language processing and content analysis [K-means algorithm]

Twitter

Rosado, L., Da Costa, J.M.C., Elias, D. & Cardoso, J.S. ⁷⁶

SL [SVM]

Data collection and image processing

Fast, S. et al.⁷⁷

SL [Random Forest]

Social media and News

Oyebode, O. & Orji, R. ⁷⁸

SL [Binarized Naive Bayes]

Nairaland

Zhao, O.S. et al.⁷⁹

DL [CNNs]

Screening for malaria

Oladeji, O. et al.⁸⁰

SL [SVM, Random Forest, Gradient boosting]

Google

Yang, A. et al.⁸¹

Artificial neural network [Kankanet]

Microscope

Mejía, K., Viboud, C. & Santillana, M. ⁸²

SL [AutoRegression and Regression on Google query volumes]

Google

Aiken, E. L. et al.⁸³

SL [AutoRegression and Regression on Google query volumes]

Google

Nsoesie, E. O., Oladeji, O., Abah, A. S. A. & Ndeffo-Mbah, M. L. ⁸⁴

SL [RF regression, and SVR]

Google

Abebe, R. et al.⁶²

SL] and Topic Modeling[Logistic regression, Latent Dirichlet Allocation]

Bing

Olukanmi, S. O., Nelwamondo, F.V., & Nwulu, N. I. ⁸⁵

DL & Regression [Long Short-term Memory, Feedforward Neural Networks (FNN), Elastic Net, SVM, Multiple Linear Regression]

Google

Tudor C. & Sova R. ⁸⁶

SL [Neural Network Autoregression]

Google

Adamu, H. et al.⁸⁷

SL [Multinomial Naïve Bayes, SVM, Random Forest, Logistics Regression, KNN, Decision Tree]

Twitter

Majam, M. et al.⁸⁸

SL [Logistic Generalized Linear Models, Bayesian Generalized Linear Models, Lasso Regression, SVMs, Decision Trees, and Gradient Boosted Decision Trees]

Data collection via survey

Maffioli, E. M. & Gonzalez, R. ⁸⁹

SL [Random Forest Regression, Least Absolute Shrinkage and Selection Operator (LASSO)]

Data collection via survey

Potgieter, A. et al. ⁹⁰

UnSL [Principal Component Analysis, Hierarchical Clustering]

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