Healthy Pathways
University of Malta (Valletta Campus)
Featured Supporting Thinking Machines with FAIRness: A New Kind of Science in Society View Digital Media
Paper Presentation in a Themed Session Francisca Onaolapo Oladipo
Beyond the development of a thinking machine, there is also the need to validate the model to check the accuracy and ensure the prediction quality in real-life. Given that a thinking machine is as smart as the data it is trained with, there is the need for an infrastructure to support the production of training and validation data that have provenance. This proposal makes a case for the need to support the discovery of Southern Knowledge through proper research management. To support thinking machines with a formal process for the collection, annotation, and archiving of data. To preserve valuable digital assets, including southern knowledge, and ensure that they are discoverable and re-useable for downstream investigations, alone, or in combination with newly generated knowledge. This can be achieved through a new kind of science in society. The kind of Science that ask the questions of: How do we provide access to critical data across locations? How do we ensure that the data is ’official’? How do we ensure data governance? How do we protect data ownership? How do we ensure that all Research data remains: Findable, Accessible, Interoperable, and Reusable (FAIR)?
Adoption of an Innovative Digital Health Solution for Children Living with Type 1 Diabetes View Digital Media
Paper Presentation in a Themed Session Anila Virani
TrustSphere is a novel, secure integrated data-driven platform that aims to streamline clinical care delivery among children living with Type 1 Diabetes (T1D) and their families. We share the results of the first round of usability testing in the initial co-development phase of TrustSphere, focused on identifying potential barriers and facilitators for the adoption of such technology. Parents of children living with T1D were invited to participate in reviewing the initial prototypes of the TrustShpere during video-recorded online sessions. We used a hybrid approach to testing comprised of rapid iterative analysis through agile methodology in collaboration with industry partners and thematic analysis to identify higher-level themes. In February-March 2021, seven parents participated in the first round of testing. Two main factors emerged that influenced parents’ potential adoption of TrustSphere: 1) users’ understanding of the added value of an integrated digital health solution and 2) the importance of integrating digital health literacy when navigating through the app features. The abundance of apps available to the public can be overwhelming to users. Many users are already utilizing apps to support aspects of their diabetes management. Adjusting to another app requires time and effort and users need to understand the value of an app before its implementation in their care experience. Our findings suggest that highlighting the added value of using TrustSphere for diabetes management to users and implementing language that is preferred by users are important factors to optimize buy-in and adoption.
The Microfluidic Nanotechnology Generates Knowledge to Benefit Cancer Patients : Microfluidic Single Cell Assay Generates Multidrug Resistance Knowledge View Digital Media
Paper Presentation in a Themed Session Paul Chi Hang Li
We have employed the biochip to conduct single cell analysis for cancer research. The analysis is enhanced by the knowledge of microfluidics and nanotechnology to measure cancer cells. The epistemology in science and medicine generates the data and metadata of multidrug resistance (MDR) in cancer cells of patients. MDR, which is one of the major obstacles in drug delivery in cancer treatment, may be overcome by using MDR inhibitors, thus facilitating treatment and benefiting cancer patients in the society. The data and metadata of MDR assist doctors and clinicians as the knowledge end-users to make informed clinical decisions. The data also benefit drug discovery of pharmaceutical end-users and assist in patient selection for clinical drug trials. The boundaries, limitations, strengths, functions and ownership of knowledge of the MDR data are also discussed.
