Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Artificial Intelligence for Population Health and Wellness
0
Zitationen
9
Autoren
2026
Jahr
Abstract
Population health management (PHM) employs a proactive approach to enhance healthcare outcomes by addressing community-wide health concerns. This method involves identifying at-risk individuals, implementing targeted interventions, and considering broader social determinants of health. Artificial intelligence (AI) plays a crucial role in improving PHM by processing vast datasets, forecasting health risks, and facilitating personalized healthcare plans. Unlike traditional techniques, AI can identify intricate risk patterns that might be overlooked, leading to more accurate risk stratification and tailored intervention measures. Notwithstanding its advantages, there are drawbacks to integrating AI into PHM, such as the need for algorithmic transparency and data protection issues. The ethical, practical, and widespread adoption of AI-driven PHM systems will depend on how well these issues are resolved.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.312 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.169 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.564 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.466 Zit.