Deep neural networks (DNNs) have become a cornerstone of modern AI technology, driving a thriving field of research in ...

A recent analysis of a major developmental dataset reveals that children who play musical instruments over several years ...

This project demonstrates the application of various machine learning algorithms for heart disease classification. By comparing the performance of SVM, MLP, and Random Forest models, we can determine ...

Background: Alterations in brain structure have been suggested to be associated with bulimia nervosa (BN). This study aimed to employ machine learning (ML) methods based on diffusion tensor imaging ...

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...

Abstract: Classification tasks have long been a central concern in the field of machine learning. Although deep neural network-based approaches offer a novel, versatile, and highly precise solution ...

tweet_classification/ │ ├── data/ # CSV dataset files │ └── labeled_data.csv │ ├── models/ # Contains each model's training function │ ├── knn_model.py │ ├── svm_model.py │ ├── ...

1 San Juan Bautista School of Medicine, Caguas, Puerto Rico, United States 2 Independent Researcher, Monmouth County, NJ, United States Background: In many countries, patients with headache disorders ...

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.

Forbes contributors publish independent expert analyses and insights. Writes about the future of finance and technology, follow for more. We live in a world where machines can understand speech, ...