This paper proposes a structure and method for the development of an AI diagnostic system as a highly leveraged step toward improvements in delivery of healthcare in underserved regions. First, the paper provides a high-level, general review of the current efforts to provide healthcare services in underserved areas and the many efforts being made to impact health outcomes by various international, governmental, and NGO entities. We also very briefly review university programs and research institutions that have specific technical and institutional assets with significant potential to carry out research or to partially implement such a plan. Our review uses weighted values in a decisionsystem that takes in a variety of assets we consider fundamental to successful engagement in delivery of new, innovative, technology-enabled healthcare systems for underresourced settings. We then review nine factors that hinder the advancement in healthcare in under-resourced settings, some of which are well described in current literature and some that may bring new perspectives. The paper then attempts to review how a proposed system can manage to operate successfully within the context of the nine named hindrance factors. The primary focus of the paper is in the description of a system which can increase the availability of diagnostics through technology-enabled systems. Such a system would impact the outcomes of persons in underserved regions. The paper then describes why making diagnostics available is a critical priority among efforts for improvements in global health.