Building Scalable, Integrative Infrastructure to Harmonize Healthcare and Genomic Data for Clinical Decision Support

Infectious diseases, such as sepsis, can be life-threatening in the absence of timely administration of appropriate treatments. These diseases result from pathogenic infections, with disease progression influenced by complex interactions between the host and the infecting agent. Machine learning, offer potential for early identification by leveraging integrated datasets that encompass both patient responses from institutional health records and pathogen-specific infection factors. To facilitate such applications, we developed a comprehensive framework utilizing this integrated data to support efficient modelling processes. To the best of our knowledge, this represents the first dedicated framework designed for the unique challenges of healthcare data modelling.