A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic ...

Background Suicide rates have increased over the last couple of decades globally, particularly in the United States and among populations with lower economic status who present at safety-net ...

Introduction: Accurate identification of forest tree species is essential for sustainable forest management, biodiversity assessment, and environmental monitoring. Urban forests, in particular, ...

DiseaseX is a state-of-the-art healthcare platform that leverages machine learning to provide accurate disease predictions and health analysis. Our platform integrates multiple specialized models to ...

Background: Decisions surrounding involuntary psychiatric treatment orders often involve complex clinical, legal, and ethical considerations, especially when patients lack decisional capacity and ...

ABSTRACT: In this study, multi-source remote sensing data and machine learning algorithms were used to delineate the prospect area of remote sensing geological prospecting in eastern Botswana. Landsat ...

The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate.

In this study, multi-source remote sensing data and machine learning algorithms were used to delineate the prospect area of remote sensing geological prospecting in eastern Botswana. Landsat 8 remote ...

Abstract: With the use of a Novel Random Forest Classifier with K-Fold Cross Validation and a comparison of the findings with those of a Stochastic Gradient Classifier for the Chicago Crime dataset, ...