A Methodological framework to Integrate AGI into Personalized Healthcare
Sajib Alam
Software Engineer, Trine University
Keywords: Artificial General Intelligence (AGI), Personalized healthcare, Methodological framework, Healthcare systems, Ethical considerations
Abstract
The integration of artificial general intelligence (AGI) into personalized healthcare represents a transformative approach to modernizing medical services, offering unprecedented improvements in patient outcomes, efficiency, and accessibility. This paper proposes a comprehensive methodological framework for the adoption of AGI within healthcare systems, addressing the intricate challenges and vast opportunities presented by AGI technologies. By examining the current landscape of AI and AGI, the paper underscores the potential of AGI to enhance diagnostics, patient care, and the personalization of treatment plans through its superior data processing and decision-making capabilities. The proposed framework emphasizes a structured integration process, including the assessment of healthcare needs alongside AGI capabilities, the establishment of robust data management and governance, and the development and validation of AGI systems tailored to healthcare applications. Moreover, it highlights the importance of ethical considerations, regulatory compliance, and the need for ongoing evaluation and adaptation of AGI technologies to ensure they align with the highest standards of patient care. Through this framework, the paper aims to provide actionable insights for healthcare professionals, informaticians, and policymakers, facilitating the ethical and effective adoption of AGI in healthcare settings and paving the way for a future where personalized healthcare is accessible to all.
Author Biography
Sajib Alam, Software Engineer, Trine University
