New AI model decodes brain signals captured noninvasively via EEG opens the possibility of developing future neuroprosthetics ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

These new AI assistants can analyze design constraints and create custom machine learning models as well as read, import and ...

A signal-processing–based framework converts DNA sequences into numerical signals to identify protein-coding regions. By integrating spectral analysis and SVM classification, the approach improves ...

Schizophrenia is a severe and often highly debilitating psychiatric disorder characterized by distorted emotions, thinking patterns and altered perceptions of reality, as well as mental impairments.

As AI adoption accelerates faster than regulation, Alexander Schlager of Aiceberg.ai argues that transparent, explainable AI ...

In a study titled Recent Applications of Machine Learning Algorithms for Pesticide Analysis in Food Samples, published in the ...

Artificial intelligence is reshaping cybersecurity, but much of that progress has focused on cloud and enterprise ...

Why Are Machine Identities Essential for Data Security in the Cloud? Where cloud environments have become the backbone of modern enterprises, securing data requires more than just human oversight.

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

Are You Leveraging Agentic AI for Enhanced Financial Security? Businesses across various sectors are increasingly relying on Agentic AI to bolster their financial security measures. But what exactly ...

EEG-based machine learning predicted SSRI treatment response in depression with high accuracy. Learn how brain signals could ...