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

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

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

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

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

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Representative photographic image. by Kengo Oka (1420585)

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

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

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

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

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

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DataSheet_1_Raman Spectroscopic Differentiation of Streptococcus pneumoniae From Other Streptococci Using Laboratory Strains and Clinical Isolates.pdf by Marcel Dahms (9160118)

“…Improvement of the classification rate is expected with optimized model parameters and algorithms as well as with a larger spectral data base for training.…”

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

“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”

Image4_Automatic recognition of complementary strands: lessons regarding machine learning abilities in RNA folding.png by Simon Chasles (16927875)

Image1_Automatic recognition of complementary strands: lessons regarding machine learning abilities in RNA folding.png by Simon Chasles (16927875)

Image2_Automatic recognition of complementary strands: lessons regarding machine learning abilities in RNA folding.png by Simon Chasles (16927875)

Image3_Automatic recognition of complementary strands: lessons regarding machine learning abilities in RNA folding.png by Simon Chasles (16927875)

<i>hi</i>PRS algorithm process flow. by Michela C. Massi (14599915)

Data Sheet 1_Bundled assessment to replace on-road test on driving function in stroke patients: a binary classification model via random forest.docx by Lu Huang (211625)

“…The subject was classified as either Success or Unsuccess group according to whether they had completed the on-road test. A random forest algorithm was then applied to construct a binary classification model based on the data obtained from the two groups.…”

A radar plot illustrating the comparison of the classification accuracy, cost values, and fitness values for the hybrids of BEOSA when applied to some high-dimensional datasets usi... by Olaide N. Oyelade (14047002)

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