Keywords: Synthetic, Simulation, MultiModalData
Need: SyntheaTM is an open-source, synthetic patient generator that models the medical history of synthetic US patients. The data science team are currently amending this codebase into a UK-based version with the vision of using this to create electronic health records across primary, secondary and community care for a defined population. These records would then act as a synthetic view of the system enabling faster innovation and easier demonstration for population health.
This project would seek to build a secondary downstream codebase to add multimodal generation . This could come in the form of generating unstructured text in different forms (e.g. Patient letters) using the information generated in the simulation or creating relevant images (e.g. MRI scan) based on the activities the patient has undergone. It’s envisaged that current generation solutions could be used to create medium fidelity
Current Knowledge/Examples & Possible Techniques/Approaches:
Related Previous Internship Projects: n/a but our current development is open here
Enables Future Work: Use of Synthea for generating synthetic longitudinal patient records
Outcome/Learning Objectives:
Datasets: n/a
Desired skill set: When applying please highlight any experience around work with pathways or longitudinal data, software development, synthetic generation of text and/or images, coding experience (including any coding in the open), and any other data science experience you feel relevant.
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