Generative AI may significantly reduce the number of animal experiments

In early phases of drug development, new active substances are tested in animals—alongside numerous other experimental ...
IEEE

High-Fidelity EEG Generation: Generative Adversarial Network Highlighting Time-Frequency-Spatial Features Regulated by Global Dynamics Supervision

Abstract: Electroencephalogram (EEG) analysis has heavily relied on sophisticated machine learning methods. However, the limited availability of diverse and extensive EEG datasets often underscores ...

So you’ve heard these AI terms and nodded along; let’s fix that

The rise of AI has brought an avalanche of new terms and slang. Here is a glossary with definitions of some of the most ...
IEEE

Adversarial Machine Learning in Cybersecurity: Attacks, Defenses, Robustness, and Explainability

Abstract: Most modern cybersecurity systems, including intrusion detection, malware classification, anomaly detection, and authentication, utilize machine learning. However, ML models are susceptible ...
IMD business school

AI trends in pharma: From R&D to operational efficiency and accuracy for competitive advantage

The use of AI in drug discovery and development helps accelerate timelines for clinical trials and expand the search for viable compounds. Pharma’s current focus on efficiency risks overlooking AI’s ...