Gen-AI Perspective in Digital Healthcare: Ownership versus Practicality

The practical implementation and data ownership implications of artificial intelligence (AI) integration in digital healthcare is investigated in this article. It suggests conceptualizing every patient as a complex data structure to facilitate the implementation of personalized medicine. This, however, poses privacy and commercialization-related ethical concerns. The article emphasizes the capacity of artificial intelligence to enhance diagnosis and treatment via the analysis of massive datasets. However, obstacles persist concerning bias, transparency, and human oversight. It provides the conversion of MRI to CT scans via generative adversarial networks as an illustration of the utility of AI. Work remains, nevertheless, to guarantee that AI advances health equity. It is concluded in the paper that continuous research and stakeholder collaboration are required to strike a balance between technological advancement and patient rights. Additional research is necessary in privacy protection, human-AI interaction, and bias mitigation as the healthcare industry undergoes digital transformation.