Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
The doctor and patient of tomorrow: exploring the intersection of artificial intelligence, preventive medicine, and ethical challenges in future healthcare
12
Zitationen
2
Autoren
2025
Jahr
Abstract
Artificial intelligence (AI) 's rapid integration into healthcare transforms medical decision-making, preventive strategies, and patient engagement. AI-driven technologies, including real-time health monitoring and predictive analytics, offer new personalized preventive care possibilities. However, concerns regarding ethical implications, data security, and equitable access remain unresolved. This paper addresses the critical gap in AI integration in preventive healthcare, highlighting statistical evidence of its impact. It also explores the intersection of AI, preventive medicine, and ethical challenges in future healthcare, envisioning the evolving roles of physicians and patients in an AI-integrated ecosystem. A fictional case study projected for 2040, illustrating an entirely digitized, AI-supported healthcare system, frames the discussion about digital health technologies, privacy regulations, and AI's ethical implications in the future of preventive medicine. Digital health interventions powered by AI will facilitate real-time preventive strategies, strengthen patient autonomy, and enhance precision medicine. However, algorithmic bias, data privacy, and healthcare equity challenges must be addressed to ensure AI fosters inclusivity rather than exacerbating disparities. Regulatory frameworks, such as GDPR, provide foundational protections, but further adaptations are required to govern AI's expanding role in medicine. This digital-assisted preventive medicine has the potential to redefine patient-provider interactions, enhance healthcare efficiency, and promote proactive health management. However, achieving this vision requires a multidisciplinary approach involving health professionals, policymakers, and technology developers. Future research should focus on regulatory strategies, digital literacy, and ethical AI implementation to balance innovation with equity, ensuring that digital healthcare remains patient-centered and inclusive.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.197 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.047 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.410 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 · 5.410 Zit.