ROC curve for binary classification. حسب Nicodemus Songose Awarayi (18414494)

"…The model further showed superior results on binary classification compared with existing methods. …"

Confusion matrix for binary classification. حسب Nicodemus Songose Awarayi (18414494)

"…The model further showed superior results on binary classification compared with existing methods. …"

Applying the proposed image enhancement algorithm. حسب Nicodemus Songose Awarayi (18414494)

Performance metrics for random forest binary classification models. حسب Alex P. Lind (6945287)

Testing results for classifying AD, MCI and NC. حسب Nicodemus Songose Awarayi (18414494)

"…The model further showed superior results on binary classification compared with existing methods. …"

Summary of existing CNN models. حسب Nicodemus Songose Awarayi (18414494)

"…The model further showed superior results on binary classification compared with existing methods. …"

The overview of the proposed method. حسب Seyed Mahdi Hosseiniyan Khatibi (16791475)

"…<p>Five main steps, including reading, preprocessing, feature selection, classification, and association rule mining were applied to the mRNA expression data. 1) Required data was collected from the TCGA repository and got organized during the reading step. 2) The pre-processing step includes two sub-steps, nested cross-validation and data normalization. 3) The feature-selection step contains two parts: the filter method based on a t-test and the wrapper method based on binary Non-Dominated Sorting Genetic Algorithm II (NSGAII) for mRNA data, in which candidate mRNAs with more relevance to early-stage and late-stage Papillary Thyroid Cancer (PTC) were selected. 4) Multi-classifier models were utilized to evaluate the discrimination power of the selected mRNAs. 5) The Association Rule Mining method was employed to discover the possible hidden relationship between the selected mRNAs and early and late stages of PTC firstly, and the complex relationship among the selected mRNAs secondly.…"

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

"…The dataset was created, and AI-based binary classification models for malocclusion were developed using an automated machine learning platform (DataRobot) to construct three algorithms for determining malocclusion (deep bite, maxillary protrusion, and crowding). …"

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

"…The dataset was created, and AI-based binary classification models for malocclusion were developed using an automated machine learning platform (DataRobot) to construct three algorithms for determining malocclusion (deep bite, maxillary protrusion, and crowding). …"

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

"…The dataset was created, and AI-based binary classification models for malocclusion were developed using an automated machine learning platform (DataRobot) to construct three algorithms for determining malocclusion (deep bite, maxillary protrusion, and crowding). …"

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

"…The dataset was created, and AI-based binary classification models for malocclusion were developed using an automated machine learning platform (DataRobot) to construct three algorithms for determining malocclusion (deep bite, maxillary protrusion, and crowding). …"

Data Sheet 1_Bundled assessment to replace on-road test on driving function in stroke patients: a binary classification model via random forest.docx حسب 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.…"

Presentation_1_Classification of expert-level therapeutic decisions for degenerative cervical myelopathy using ensemble machine learning algorithms.pdf حسب Dougho Park (9566450)

"…We performed the following classifications using ML algorithms: multiclass, one-versus-rest, and one-versus-one. …"

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

"…</p><p>Conclusions</p><p>Supervised ML based NLP algorithms are useful for automatic classification of brain MRI reports for identification of AIS patients. …"

The data processing and analysis pipeline. حسب Xin Zhang (35492)

Development and validation of an electronic health record-based algorithm for identifying TBI in the VA: A VA Million Veteran Program study حسب Victoria C. Merritt (8581929)

"…Given its strong classification metrics, the TBI-PheCAP algorithm is recommended for use in future population-based TBI research.…"

Data XGBOOST. حسب Xin Zhang (35492)

"…Extreme Gradient Boosting (XGBoost), a machine learning algorithm, was employed for binary classification (low-moderate vs. high physical activity). …"

Data_Sheet_2_Predicting Axial Length From Choroidal Thickness on Optical Coherence Tomography Images With Machine Learning Based Algorithms.docx حسب Hao-Chun Lu (12965318)

"…We used five machine-learning base algorithms to construct the classifiers. This study trained and validated the models to classify the AXLs eyes based on binary (AXL < or > 26 mm) and multiclass (AXL < 22 mm, between 22 and 26 mm, and > 26 mm) classifications.…"

Data_Sheet_1_Predicting Axial Length From Choroidal Thickness on Optical Coherence Tomography Images With Machine Learning Based Algorithms.docx حسب Hao-Chun Lu (12965318)

"…We used five machine-learning base algorithms to construct the classifiers. This study trained and validated the models to classify the AXLs eyes based on binary (AXL < or > 26 mm) and multiclass (AXL < 22 mm, between 22 and 26 mm, and > 26 mm) classifications.…"

DataSheet1_Exploring the Common Mechanism of Fungal sRNA Transboundary Regulation of Plants Based on Ensemble Learning Methods.docx حسب Junxia Chi (12075389)