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The Race of Artificial Intelligence in Healthcare Competition and Its Impact on Human Health

2025·1 Zitationen·International Journal of Diabetes and TechnologyOpen Access
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1

Zitationen

10

Autoren

2025

Jahr

Abstract

The integration of artificial intelligence (AI) into health care has revolutionized clinical diagnostics, treatment protocols, and patient management. AI-driven innovations enhance medical efficiency, enabling precision medicine, and automating administrative workflows. However, this rapid advancement has triggered an intensely competitive race among multinational corporations, research institutions, and startups, each striving for dominance in AI-driven healthcare solutions. For example, Google’s DeepMind, IBM Watson Health, and various biotech firms have been engaged in AI-driven drug discovery and diagnostics, leading to significant market consolidation. This review explores the evolving landscape of AI in healthcare, addressing the economic, geopolitical, and regulatory factors that shape its trajectory. It critically examines intellectual property conflicts, ethical dilemmas, and disparities in AI deployment, highlighting concerns over algorithmic bias, data accessibility, and the monopolization of healthcare technologies. For instance, the acquisition of AI-powered healthcare startups by major tech companies limits competition and data access, thereby restricting innovation. Furthermore, the study underscores the societal trust challenges posed by AI’s “black box” decision-making and the ambiguity surrounding legal accountability. While AI presents unparalleled opportunities for improving global healthcare, its long-term impact hinges on balancing innovation with ethical governance, equitable access, and patient-centered medical care. Real-world AI successes, such as AI-assisted radiology tools improving early cancer detection and machine learning models optimizing personalized diabetes management, demonstrate AI’s potential benefits. This review calls for transparent AI policies, robust regulatory frameworks, and fair data-sharing initiatives to ensure AI serves as a tool for advancing public health rather than a vehicle for corporate or geopolitical supremacy.

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