Antimicrobial resistance (AMR) is an increasingly dangerous problem affecting global health. In 2019 alone, methicillin-resistant Staphylococcus aureus (MRSA) accounted for more than 100,000 global ...

Abstract: In this paper, an overview of the use of machine learning algorithms on autonomous robotic systems is presented. The concept of hardware and software integration and development is explained ...

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...

The workflow encompasses patient datacollection and screening, univariate regression analysis for initial variable selection, systematic comparison of 91 machine learning models,selection and ...

Researchers analyzed clinical data and RNA expression from the peripheral blood of 174 patients with gout and hyperuricemia that had been collected at week 48 of their participation in the STOP Gout ...

Dario Amodei, the C.E.O. of the artificial-intelligence company Anthropic, has been predicting that an A.I. “smarter than a Nobel Prize winner” in such fields as biology, math, engineering, and ...

An artificial-intelligence algorithm that discovers its own way to learn achieves state-of-the-art performance, including on some tasks it had never encountered before. Joel Lehman is at Lila Sciences ...

Abstract: This paper provides a comprehensive review of the evolution of artificial intelligence from early symbolic, rule-based systems to modern large language models (LLMs) and retrieval-augmented ...

ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...

On a scorching July afternoon in Shanghai, dozens of Chinese students hunch over tablet screens, engrossed in English, math and physics lessons. Algorithms track every keystroke, and the seconds spent ...