The Role of AI in Shifting Healthcare Paradigms: Moving from Human-Centric to Data-Centric Decision-Making
Keywords:
Artificial Intelligence (AI), data-centric decision-making, healthcare transformation, machine learning, personalized medicine, predictive analytics, clinical decision support, medical diagnostics, healthcare automationAbstract
Artificial Intelligence (AI) is rapidly transforming healthcare by shifting decision-making processes from human-centric to data-centric paradigms. This paper explores the evolving role of AI in healthcare, focusing on how data-driven models are enhancing diagnostic accuracy, treatment personalization, and operational efficiency. By leveraging vast amounts of medical data, AI algorithms, particularly in machine learning and deep learning, are enabling healthcare systems to deliver more precise and predictive care, significantly reducing human error and cognitive overload. Furthermore, AI's integration into healthcare is reshaping clinical workflows, improving patient outcomes, and optimizing resource allocation. Despite these advancements, challenges related to data privacy, ethical considerations, and the integration of AI into existing systems persist. This paper examines these challenges while highlighting the potential for AI to revolutionize healthcare through evidence-based, data-centric approaches. The implications of this shift for healthcare providers, patients, and the overall health ecosystem are also discussed, underscoring AI's role as a transformative force in the future of healthcare delivery.
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Copyright (c) 2020 Ankita Behera (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
