Image Exchange: IHE and the Evolution of Image Sharing
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
The sharing of radiologic images has become a fundamental part of radiology services and is essential for delivering high-quality care. Film is quickly becoming obsolete as a means of transporting and sharing large volumes of imaging data. Image sharing has evolved from film to transportable media (eg, compact disks) to direct electronic exchange over the Internet. The latter two means of image sharing have associated work flow-related and technical challenges for which solutions are being developed. Integrating the Healthcare Enterprise (IHE) provides a standards-based approach to the development of robust, universally accepted solutions. Several IHE profiles have been developed to provide a framework for current image sharing efforts. The Philadelphia and New Jersey Health Information Exchanges and the Canada Health Infoway represent efforts to apply IHE technical profiles to facilitate the secure and confidential exchange of electronic images over the Internet. The research community is concomitantly developing solutions that solve image exchange issues that are specific to research (eg, the sharing of deidentified data) but that might also be encountered in the general population. The personal health record is a more recent development that may provide consumers with direct control over the process of sharing images electronically with their healthcare providers.
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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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