In machine learning, privacy risks often emerge from inference-based attacks. Model inversion techniques can reconstruct sensitive training data from model outputs. Membership inference attacks allow ...
In the first instalment of LCGC International's interview series exploring how artificial intelligence (AI)/machine learning ...
The March 2026 issue of NEJM Catalyst Innovations in Care Delivery is a special theme issue on the hard work of implementing artificial intelligence in real-world ...
Enterprise adoption of cognitive intelligence platforms has accelerated, yet executive confidence has not kept pace. Many deployments promise ...
To prevent algorithmic bias, the authors call for multivariable modeling frameworks that jointly incorporate biological sex, genetic ancestry, and gender-related life-course exposures.
Introduction The proliferation of deepfake technology, synthetic media generated using advanced artificial intelligence techniques, has emerged as a ...
Artificial Intelligence, Augmented reality, Blockchain, Customer Experience, Data-Driven Decisions, Future of retail, retail ...
A new study introduces a global probabilistic forecasting model that predicts when and where ionospheric disturbances—measured by the Rate of total electron content (TEC) Index (ROTI)—are likely to ...
With the rise of ransomware, phishing, zero-day exploits and other cyberthreats, organizations worldwide are confronting a cybersecurity crisis that ...
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