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Data science is about organizing it, looking for patterns, and using those patterns to understand what is happening and what might happen next." Michigan Tech students like Felicia Huffman, a data ...

Dynamic predictive modeling using electronic health record data has gained significant attention in recent years. The reliability and trustworthiness of such models depend heavily on the quality of ...

Abstract: A distributed data service model integrating MySQL, Redis Sentinel, and MyCat is proposed to tackle performance bottlenecks and availability issues in high-concurrency e-commerce systems.

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Dany Lepage discusses the architectural ...

The potential applications of DTs extend beyond individual patient care to public health surveillance, hospital resource management, and epidemiological modeling. However, several challenges persist, ...

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.

Abstract: Data-driven Quality of Experience (QoE) modeling using Machine Learning (ML) is a key enabler for future communication networks as it allows accelerated and unbiased QoE modeling while ...