首页|University of Cagliari Researcher Updates Current Data on Machine Learning (Context-Aware Behavioral Tips to Improve Sleep Quality via Machine Learning and Large Language Models)

University of Cagliari Researcher Updates Current Data on Machine Learning (Context-Aware Behavioral Tips to Improve Sleep Quality via Machine Learning and Large Language Models)

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2024 FEB 20 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on artificial intelligence is the subject of a new report. According to news reporting originating from Cagliari, Italy, by NewsRx correspondents, research stated, “As several studies demonstrate, good sleep quality is essential for individuals’ well-being, as a lack of restoring sleep may disrupt different physical, mental, and social dimensions of health.” Financial supporters for this research include National Recovery And Resilience Plan. Our news journalists obtained a quote from the research from University of Cagliari: “For this reason, there is increasing interest in tools for the monitoring of sleep based on personal sensors. However, there are currently few context-aware methods to help individuals to improve their sleep quality through behavior change tips. In order to tackle this challenge, in this paper, we propose a system that couples machine learning algorithms and large language models to forecast the next night’s sleep quality, and to provide context-aware behavior change tips to improve sleep. In order to encourage adherence and to increase trust, our system includes the use of large language models to describe the conditions that the machine learning algorithm finds harmful to sleep health, and to explain why the behavior change tips are generated as a consequence. We develop a prototype of our system, including a smartphone application, and perform experiments with a set of users.”

University of CagliariCagliariItalyEuropeCyborgsEmerging TechnologiesMachine Learning

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Feb.20)
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