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 ...

Whole-mount 3D imaging at the cellular scale is a powerful tool for exploring complex processes during morphogenesis. In organoids, it allows examining tissue architecture, cell types, and morphology ...

Scientists are using machine learning to find new treatments among thousands of old medicines.

Machine learning models analyze complex patterns within medical datasets, enabling precise prediction and classification of diseases like CHD [14]- [18]. This study explores the application of three ...

Support Vector Machines (SVMs) are a powerful and versatile supervised machine learning algorithm primarily used for classification and regression tasks. They excel in high-dimensional spaces and are ...

Researchers identified three distinct autism subtypes in males, each with unique brain connectivity patterns and related behavioral traits, suggesting that tailored interventions could better address ...

Three ML algorithms were employed for data modeling: Gradient boosting (GB), support vector machine learning (SVM), and logistic regression (LR). Models were run with default parameters, except for ...

In recent years, on the basis of statistical learning theory, support vector machine (SVM) have developed vigorously, showed unique advantages in solving small sample, nonlinear and high-dimensional ...