A5013947806- Sleep and related disorders
- Recommender Systems and Techniques
- Topic Modeling
- Natural Language Processing Techniques
- Obstructive Sleep Apnea Research
- Neuroscience of respiration and sleep
- AI in Service Interactions
- Multi-Agent Systems and Negotiation
- Sleep and Work-Related Fatigue
- Advanced Graph Neural Networks
- Advanced Technologies in Various Fields
Fujian Medical University
2024
Traditional recommender systems usually take the user-platform paradigm, where users are directly exposed under control of platform's recommendation algorithms. However, defect algorithms may put in very vulnerable positions this paradigm. First, many sophisticated models often designed with commercial objectives mind, focusing on benefits, which hinder their ability to protect and capture users' true interests. Second, these typically optimized using data from all users, overlook individual...
Age, gender, body mass index (BMI), and mean heart rate during sleep were found to be risk factors for obstructive apnea (OSA), a variety of methods have been applied predict the occurrence OSA. This study aimed develop evaluate OSA prediction models using simple accessible parameters, combined with multiple machine learning algorithms, integrate them into cloud-based mobile medicine management platform clinical use. The data obtained from records 610 patients who underwent polysomnography...
Background: The sleep quality of medical staff was severely affected during COVID-19, but the factors influencing frontline involved in assistance remained unclear, and screening tools for their were lacking. Methods: From June 25 to July 14, 2022, we conducted an Internet-based cross-sectional survey. Pittsburgh Sleep Quality Index (PSQI), a self-designed general information questionnaire, questionnaire regarding combined understand Fujian Province supporting Shanghai past month. A...
<sec> <title>UNSTRUCTURED</title> Background: Age, gender, body mass index (BMI), and mean heart rate during sleep were found to be risk factors for obstructive apnea (OSA), a variety of methods have been applied predict the occurrence OSA. Objective: This study aimed develop evaluate OSA prediction models using simple accessible parameters, combined with multiple machine learning algorithms, integrate them into cloud-based mobile medicine management platform clinical use. Methods: The data...