Resource-limited settings (RLS) are characterised by lack of access to adequate resources such as ICT infrastructure, qualified medical personnel, healthcare facilities, and affordable healthcare for common people. The potential for the application of AI and clinical decision support systems in RLS are limited due to these challenges. Towards the improvement of the status quo, this chapter presents the conceptual design of a framework for the semantic integration of health data from multiple sources to facilitate decision support for the diagnosis and treatment of gait-related diseases in RLS. The authors describe how the framework can leverage ontologies and knowledge graphs for semantic data integration to achieve this. The plausibility of the proposed framework and the general imperatives for its practical realisation are also presented.
A computational infrastructure for semantic data integration towards a patient-centered database for Tuberculosis care
