Store-and-forward teledermatology: a case report
Bibliographic record
Abstract
BACKGROUND: Telemedicine is increasingly being used as part of routine practice for many physicians and healthcare providers across the country. Due to its visual nature, dermatology is ideally suited to benefit from this new technology. The use of teledermatology (telemedicine in dermatology) in a primary care setting allows for an expert opinion without the need for an in-person referral. Furthermore, it can improve patient access in remote areas. Store-and-forward teledermatology is the most commonly employed method. CASE PRESENTATION: This case describes a Caucasian male in his fifties with no fixed address or telephone number who presented to his family doctor with an enlarging nevus on his chest, and required a dermatology referral. Given these limitations, a traditional fax and phone referral would not be possible. Instead store-and-forward teledermatology was employed. It was then determined by the dermatologist that the nevus was benign and did not require treatment. CONCLUSION: This case demonstrates the utility of store-and-forward teledermatology in what is unfortunately not an uncommon scenario in Canada. The patient was successfully managed, and a logistically difficult and expensive in-person referral was avoided.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".