SOPHRA: A Mobile Web Services Hosting Infrastructure in mHealth
Bibliographic record
Abstract
The use of mobile devices such as smartphones and tablets, and other ICT tools to facilitate healthcare delivery in the medical landscape, known as mHealth, has witnessed a phenomenal rise recently. In most mHealth systems, mobile devices are employed as services and health information client consumers. Thus, healthcare professionals use these devices to consume services which are running on back-end platforms. However, in a research collaboration with the Geriatrics Ward of the City Hospital in Saskatoon, Canada, we have identified a huge potential in facilitating the mobile device as a service hosting node. Hence, we developed a physically distributed information infrastructure, called SOPHRA, which aids the healthcare professionals to securely access and share patients' medical information which are hosted on their mobile devices. Since mobile devices establish communication over wireless channels which can sometimes be unavailable, the proposed mobile hosting framework faces the challenge of reliable and real-time message propagation to the mobile participants. This paper presents the adopted methodologies employed in implementing SOPHRA to address the aforementioned challenges. A cloud-oriented middleware is implemented which enables the mobile participants to reliably communicate in soft real-time. Furthermore, the records of the patients are modeled as Web Services (WS) which aids medical information to be passed across the system components; and these WS are independently replicated on the middleware to ensure high information availability. Currently, SOPHRA supports both SOAP and RESTful Web Services protocols and facilitates information exchanges over Wi-Fi.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".