Our proposed Mi-Diagnosis research aims to develop cost-effective, mobile technology-based healthcare solutions that can help people manage their own health and disease outside institutions, improving health outcomes and encouraging citizens to remain healthy.
We've proposed solutions through interdisciplinary and multidisciplinary research on intelligent self-care schemes for diagnosis, and automatic generations of learning material for users to improve their understanding further, based on outcomes of the self-diagnosis schemes.
Our research includes investigations into the development of smart mobile technology-based regular diagnosis, monitoring, prognosis, personal health management and generation of learning material from internet sources for patients. These are linked with customised learning and condition diagnosis, particularly for cancer, diabetes, stroke, trauma, movement disorder, Parkinson and Alzheimer's diseases, neuropsychiatric or any other disease-related disorders.
Among various diagnosis tools, intelligent eye test (iTest) is one of the key focuses to identify various diseases linked with retinal images, identification of power of lens for a specific retinal condition and automatic frame selection based on facial structure. For further details see our recent publiucation.
Bourouis, A., Feham, M. and Zhang, L., 2014. An Intelligent Mobile based Decision Support System for Retinal Disease Diagnosis. Journal of Decision Support Systems, 59, pp.341-350.