Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Telemedicine and AI Redefining Healthcare Access and Insurance Reimbursement Models
0
Zitationen
2
Autoren
2025
Jahr
Abstract
Telemedicine combined with artificial intelligence is reshaping healthcare delivery, redefining patient access and forcing insurers to rethink reimbursement. This chapter explores how AI-driven telehealth dissolves geographic barriers, sharpens diagnostics, and tailors treatment, thereby raising quality while curbing costs. Machine-learning models, natural-language processing and predictive analytics extend telehealth's reach into preventive care, chronic-disease management and population-health initiatives. Yet these gains bring new hurdles: safeguarding data privacy, meeting evolving regulations, clarifying professional liability and designing reimbursement formulas that capture the added value of algorithm-supported care. By surveying current deployments, policy responses and cutting-edge tools, the chapter distills lessons for providers, payers and lawmakers. It closes with strategic recommendations to maximize benefits, overcome implementation barriers and guarantee equitable access to AI-enabled telemedicine.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.719 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.628 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 8.176 Zit.
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
2019 · 6.880 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.