The natural protein universe is vast, and yet, going beyond and designing new proteins not observed in nature can yield new ...

EMBL-EBI scientists and collaborators at Heidelberg University have developed CORNETO, a new computational tool that uses ...

A response to recent largesse of large language modeling material. Reading the Communications March 2025 issue, it struck me ...

Published (DOI: 10.1186/s43020-025-00167-8) on June 9, 2025, in Satellite Navigation, researchers from the Royal Observatory of Belgium and the State Key Laboratory of Precision Geodesy in China ...

This study attempts to classify precipitation using machine learning algorithms on selected meteorological data. The models used are K-nearest neighbors (KNNs), support vector machine (SVM), and ...

Mustafa Abdullah, D. and Mohsin Abdulazeez, A. (2021) Machine Learning Applications Based on SVM Classification a Review. Qubahan Academic Journal, 1, 81-90.

Conclusion Machine learning methods show promise in the prediction of prognosis (specifically functioning, relapse and remission) of mental disorders based on relevant collected variables. Future ...

Subspace learning and Support Vector Machine (SVM) are two critical techniques in pattern recognition, playing pivotal roles in feature extraction and classification. However, how to learn the optimal ...

The aim is to analyze the effectiveness of machine learning models in predicting obesity classes and to determine which model performs best in obesity classification. METHODS: We used a dataset with 2 ...

The RF method exhibited superior machine learning capabilities, as evidenced by smaller residuals (Supplementary Figures S1B–C) and higher AUC values (Supplementary Figure S2A) than those of the SVM.

Building a PC for AI or machine learning is very different from making your own gaming machine. Here are some top tips so you won't go wrong.