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ZENODO
Article . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
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AI, ML, AND VIRTUAL ASSISTANTS: A CROSS-DISCIPLINARY FRAMEWORK FOR ADVANCING ROBOTIC HEALTHCARE AND CORPORATE GOVERNANCE

Authors: Nagarjuna Reddy Aturi;

AI, ML, AND VIRTUAL ASSISTANTS: A CROSS-DISCIPLINARY FRAMEWORK FOR ADVANCING ROBOTIC HEALTHCARE AND CORPORATE GOVERNANCE

Abstract

The interdisciplinary framework that integrates AI, ML, Virtual Assistants, and neural imagingtechnologies for a complete makeover in robotic healthcare and improvement of corporate governancesystems. The research investigates various transformational applications in healthcare, such as intelligentrobotic surgeries, predictive patient monitoring, and personalized digital care. It further investigates howthese innovations improve corporate decision-making, compliance, and risk management throughintelligent automation. Governance Implications: The study identifies a number of challenges that need tobe overcome, which include integration of ethics, scalability, and cross-industry adoption. Further,strategies are proposed to develop a harmonious, technology-driven ecosystem by leveraging synergies inhealthcare advancements and improvements in corporate governance. The paper discusses how thesetechnologies may contribute toward operational efficiency, better patient outcomes, and robust governanceframeworks across industrie

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green