⚡ Quick Summary

This bibliometric analysis explores the growing role of artificial intelligence (AI) in the field of obstructive sleep apnea (OSA), revealing a significant increase in publications post-2017. The study highlights key contributors and trends, emphasizing the potential of deep learning in enhancing diagnosis and treatment strategies.

🔍 Key Details

• 📊 Dataset: 867 articles published between 2011 and 2024
• 🌍 Leading Country: China with the highest number of publications
• 🏆 Top Authors: Daniel Alvarez and Roberto Hornero
• 📖 Most Cited Work: “Estimation of the global prevalence and burden of obstructive sleep apnoea”
• 🔑 Dominant Keywords: OSA, machine learning, electrocardiography, deep learning

🔑 Key Takeaways

• 📈 Publication Growth: A steady increase in AI-related OSA research since 2017.
• 🌟 Key Institutions: Universidad de Valladolid and IEEE Journal of Biomedical and Health Informatics lead in productivity.
• 🤝 Collaboration: Emphasis on enhancing international cooperation and interdisciplinary communication.
• 🔍 Focus Areas: Diagnosis, personalized treatment, prognosis assessment, and telemedicine.
• 🚀 Future Directions: Continued exploration of AI, particularly deep learning, in OSA research.

📚 Background

Obstructive sleep apnea (OSA) is a prevalent condition that significantly impacts sleep health and overall well-being. The integration of artificial intelligence into OSA research presents an exciting opportunity to enhance diagnostic accuracy and treatment efficacy. As AI technologies evolve, their application in healthcare is becoming increasingly vital, particularly in areas requiring complex data analysis and personalized patient care.

🗒️ Study

Conducted using the Web of Science Core Collection dataset, this bibliometric analysis aimed to map the landscape of AI applications in OSA from January 2011 to August 2024. Utilizing tools like VOSviewer and Citespace, the study assessed publication trends, key contributors, and thematic keywords, providing a comprehensive overview of the current state of research in this field.

📈 Results

The analysis revealed a total of 867 articles related to AI in OSA, with a notable increase in publications after 2017. China emerged as the leading contributor, while the most prolific authors were Daniel Alvarez and Roberto Hornero. The study identified key themes, with keywords such as machine learning and deep learning dominating the discourse, indicating a shift towards advanced computational techniques in OSA research.

🌍 Impact and Implications

The findings of this study underscore the transformative potential of AI in the management of OSA. By leveraging advanced technologies, researchers and clinicians can improve diagnostic processes, tailor treatments to individual patient needs, and enhance overall sleep health. The emphasis on international collaboration and interdisciplinary communication is crucial for maximizing the benefits of AI in this field, paving the way for innovative solutions and improved patient outcomes.

🔮 Conclusion

This bibliometric analysis highlights the expanding role of artificial intelligence in obstructive sleep apnea research, particularly through the lens of deep learning. As the field continues to evolve, it is essential to foster collaboration and communication among researchers to fully harness AI’s potential in advancing sleep health. The future of OSA management looks promising, with AI poised to deliver more precise and personalized medical services to patients.

💬 Your comments

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