Dr Yamiko Msosa
Postdoctoral Research Systems Engineer
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KCL Purehttps://kclpure.kcl.ac.uk/portal/yamiko.msosa.html
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Google Scholarhttps://scholar.google.co.uk/citations?user=urKLYogAAAAJ
BIOGRAPHY
I am a digital health researcher with a PhD in Computer Science from the University of Cape Town. I have extensive technical and engineering management experience in the digital health landscape. My research interests are in the broader areas of software engineering, and in particular, model-driven engineering as it applies to health information systems engineering. I am particularly interested in how clinical practice guidelines (CPGs) can be formalized and supported in health information systems using model-driven engineering methods. I am currently focusing on interrogating digital health interventions as they apply to mental health. I am also interested in innovative approaches to indigenous knowledge documentation and preservation. I frame my research within limited-resource settings. I employ an experimental approach to computer science research that includes formal modelling, building and testing of computational artefacts.
RESEARCH INTERESTS
Clinical Informatics; Electronic Health Records; Clinical Practice Guideline Formalization; Model-driven Engineering; Software Language Formalization.
LATEST PUBLICATIONS
- Corrigendum “Anticoagulation for atrial fibrillation in people with serious mental illness in the general hospital setting"
- Anticoagulation for atrial fibrillation in people with serious mental illness in the general hospital setting
- An implementation framework and a feasibility evaluation of a clinical decision support system for diabetes management in secondary mental healthcare using CogStack
- Patient-centric characterization of multimorbidity trajectories in patients with severe mental illnesses: A temporal bipartite network modeling approach
- Corrigendum “Anticoagulation for atrial fibrillation in people with serious mental illness in the general hospital setting” [J. Psychiatr. Res. 153 (2022) 167–173, (S0022395622003508), (10.1016/j.jpsychires.2022.06.044)]