Special issue on software engineering for Connected Health: Challenges and research roadmap
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Over the past decade, there have been increasing expectations and pressures placed on health care providers to deliver more efficient, quality, and safe health care services. As a result, this shifts the balance between supply‐and‐demand of health care services. It also brings about new challenges for health care professionals' capabilities to deliver safe and quality care in a timely manner. There are significant opportunities to exploit information and communications technology and transform how health care service is provided. Connected Health is one such transformation for health care management and changes in health care practice. However, the field of Connected Health is still in its infancy. This Special Issue in Software Engineering for Connected Health begins to address this and presents 5 quality contributions to demonstrate how software engineering research plays an important role in Connected Health research. These contributions also identify the limitations of the existing theories and to develop new or revised theories of Software Engineering for Connected Health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 0.000 |
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 it