The classification algorithm flow chart for binary classification among NC, EMCI, LMCI and AD groups. حسب Qian Zhang (49333)

For each classification algorithm, the classification accuracies for binary subject groups NC versus EMCI, NC versus LEMC, EMCI versus LEMC, EMCI versus AD, LMCI versus AD, AD vers... حسب Qian Zhang (49333)

Explicability results of the crowding classification model. حسب Kengo Oka (1420585)

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Explicability results of the deep bite classification model. حسب Kengo Oka (1420585)

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Explicability results of the maxillary protrusion classification model. حسب Kengo Oka (1420585)

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Structure of the proposed hybrid CNN-SVD-based ensemble model for lung cancer classification. حسب Md. Sabbir Hossain (9958939)

Association between maxillary protrusion and oral habits. حسب Kengo Oka (1420585)

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Association between crowding and oral habits. حسب Kengo Oka (1420585)

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Guide frame that appears on the smartphone application. حسب Kengo Oka (1420585)

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Association between deep bite and oral habits. حسب Kengo Oka (1420585)

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Performance metrics of the logistic regression models on the test dataset. حسب Kengo Oka (1420585)

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Representative photographic image. حسب Kengo Oka (1420585)

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Breakdown of participants by residential area. حسب Kengo Oka (1420585)

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Flowchart of study participants and design. حسب Kengo Oka (1420585)

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Breakdown of participants by annual household income. حسب Kengo Oka (1420585)

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Performance metrics of the machine learning models on the test dataset. حسب Kengo Oka (1420585)

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Each variable for the dataset. حسب Kengo Oka (1420585)

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Random forest model performs better than support vector machine algorithms and when it primarily uses spontaneous photopic ERG of 60-s duration in humans. حسب Ramsés Noguez Imm (6658637)

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

"…The capacity to confront and overcome this obstacle is where machine learning and metaheuristic algorithms shine. This study introduces the Adaptive Dynamic Particle Swarm Optimization enhanced with the Guided Whale Optimization Algorithm (AD-PSO-Guided WOA) for rainfall prediction. …"

The AD-PSO-Guided WOA LSTM framework. حسب Ahmed M. Elshewey (21463867)

"…The capacity to confront and overcome this obstacle is where machine learning and metaheuristic algorithms shine. This study introduces the Adaptive Dynamic Particle Swarm Optimization enhanced with the Guided Whale Optimization Algorithm (AD-PSO-Guided WOA) for rainfall prediction. …"