The cost of diagnostic errors has been high in the developed world economics according to a number of recent studies and continues to rise. Up till now, a common process of performing image diagnostics for a growing number of conditions has been examination by a single human specialist (i.e., single-channel recognition and classification decision system). Such a system has natural limitations of unmitigated error that can be detected only much later in the treatment cycle, as well as resource intensity and poor ability to scale to the rising demand. At the same time Machine Intelligence (ML, AI) systems, specifically those including deep neural network and large visual domain models have made significant progress in the field of general image recognition, in many instances achieving the level of an average human and in a growing number of cases, a human specialist in the effectiveness of image recognition tasks. The objectives of the AI in Medicine (AIM) program were set to leverage the opportunities and advantages of the rapidly evolving Artificial Intelligence technology to achieve real and measurable gains in public healthcare, in quality, access, public confidence and cost efficiency. The proposal for a collaborative AI-human image diagnostics system falls directly into the scope of this program.

This article identifies the role of anti-corruption legislation in sustainable development. The descriptive approach is used to achieve the research objectives, as it is the appropriate scientific method suitable for the nature of the study subject in terms of presenting information related to combating administrative corruption. The results indicate that efforts to combat administrative corruption to achieve sustainable development in countries can only be achieved through strict legislation specialized in combating administrative corruption with the activation of accountability mechanisms in all state departments, bodies, and ministries. The results also demonstrate the alignment of the national and international efforts to reduce the phenomenon of corruption through international agreements and treaties. Towards the end, key conclusions and recommendations are also appropriately incorporated.