SINGAPORE - Many nations throughout the world have introduced some form of universal artificial intelligence (AI) workspace for healthcare, which has come as a result of disruptive technologies that use a significant amount of available data and tools established on AI techniques with the goal of simplifying people's lives. Advances in AI are increasing healthcare systems’ performance rates in distinct accesses to care, which are largely determined by care processes, such as how safe it is in the quality of doctor-patient, healer-patient, and nurse-patient relationships, administrative efficiency, the level of equity across income groups, and patient health outcomes.

An emergent system based on a neuro-symbolic interpretation learning agent applied to the healthcare environment will aim to return to the original and ultimate objective of AI by defining and designing intelligence using a universal AI workspace. However, the construction of this intelligence requires careful consideration of how it will be descriptive of this sort of system. In this case, the intelligence will be designed on the following reflections: ‘behavior,’ ‘capability,’ ‘function,’ ‘principle,’ and ‘structure,’ with the addition of universal AI workspace methodologies, and then divided into three types of communication: autonomous, high term, and low term values from and to communities around the world.

Figure 1

Communication flow centered on community values, integrating prevention and care as a core component of the healthcare system.

Figure 1 depicts a situation in which a communication based on a high-term value notion involves four entities among money that is con