THE ECONOMICS OF INTEGRATING ARTIFICIAL INTELLIGENCE WITH TRADITIONAL AND MODERN MEDICINE: OPPORTUNITIES, CHALLENGES, AND FUTURE HEALTHCARE IMPACTS – AN EMPIRICAL ASSESSMENT

This empirical assessment explores the transformative role of Artificial Intelligence (AI) in integrating traditional and modern healthcare systems to enhance diagnostics, treatment, and resource management. Valued at USD 15.1 billion in 2022, the global AI healthcare market is projected to reach USD 188 billion by 2030, with significant impacts observed in countries like India and the US, improving radiology accuracy, predictive analytics, and reducing costs. Econometric studies reveal that increased AI adoption correlates with reduced preventable mortality (by up to 0.45%) and improved patient satisfaction, alongside substantial economic benefits, including billions in savings and productivity gains. The integration of traditional knowledge systems, such as Ayurveda, with digital intelligence fosters inclusive growth and cultural resilience. Despite these opportunities, challenges persist in data privacy, algorithmic bias, regulatory delays, and financial constraints, especially in low-resource settings. Addressing these barriers through robust policies, ethical frameworks, and innovative models is essential for sustainable, equitable healthcare. Econometric models demonstrate that strategic AI implementation can optimize cost-effectiveness, improve health outcomes, and expand access, particularly in underserved regions. Ultimately, AI does not replace but augments traditional and modern medicine, driving an integrated, patient-centered, and sustainable healthcare ecosystem. Future models focusing on preventive analytics, workflow automation, and virtual care, supported by rigorous econometrics, will shape the next phase of AI-enabled medicine, ensuring equitable and environmentally responsible healthcare delivery worldwide. The study explores urgent and evolving challenges that are becoming more critical in today’s rapidly shifting and interconnected world, underscoring their relevance in the global context.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-01-01
DOI
https://doi.org/10.5281/zenodo.16901720
Primary Topic
Water Quality and Resources Studies
Type
article
Field-Weighted Citation Impact
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article

THE ECONOMICS OF INTEGRATING ARTIFICIAL INTELLIGENCE WITH TRADITIONAL AND MODERN MEDICINE: OPPORTUNITIES, CHALLENGES, AND FUTURE HEALTHCARE IMPACTS – AN EMPIRICAL ASSESSMENT

Zenodo (CERN European Organization for Nuclear Research)
Water Quality and Resources Studies
article

THE ECONOMICS OF INTEGRATING ARTIFICIAL INTELLIGENCE WITH TRADITIONAL AND MODERN MEDICINE: OPPORTUNITIES, CHALLENGES, AND FUTURE HEALTHCARE IMPACTS – AN EMPIRICAL ASSESSMENT

article en

Abstract

This empirical assessment explores the transformative role of Artificial Intelligence (AI) in integrating traditional and modern healthcare systems to enhance diagnostics, treatment, and resource management. Valued at USD 15.1 billion in 2022, the global AI healthcare market is projected to reach USD 188 billion by 2030, with significant impacts observed in countries like India and the US, improving radiology accuracy, predictive analytics, and reducing costs. Econometric studies reveal that increased AI adoption correlates with reduced preventable mortality (by up to 0.45%) and improved patient satisfaction, alongside substantial economic benefits, including billions in savings and productivity gains. The integration of traditional knowledge systems, such as Ayurveda, with digital intelligence fosters inclusive growth and cultural resilience. Despite these opportunities, challenges persist in data privacy, algorithmic bias, regulatory delays, and financial constraints, especially in low-resource settings. Addressing these barriers through robust policies, ethical frameworks, and innovative models is essential for sustainable, equitable healthcare. Econometric models demonstrate that strategic AI implementation can optimize cost-effectiveness, improve health outcomes, and expand access, particularly in underserved regions. Ultimately, AI does not replace but augments traditional and modern medicine, driving an integrated, patient-centered, and sustainable healthcare ecosystem. Future models focusing on preventive analytics, workflow automation, and virtual care, supported by rigorous econometrics, will shape the next phase of AI-enabled medicine, ensuring equitable and environmentally responsible healthcare delivery worldwide. The study explores urgent and evolving challenges that are becoming more critical in today’s rapidly shifting and interconnected world, underscoring their relevance in the global context.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 55%
Water Quality and Resources Studies
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THE ECONOMICS OF INTEGRATING ARTIFICIAL INTELLIGENCE WITH TRADITIONAL AND MODERN MEDICINE: OPPORTUNITIES, CHALLENGES, AND FUTURE HEALTHCARE IMPACTS – AN EMPIRICAL ASSESSMENT · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS