Implementing Teledermoscopy to Shorten Doctors’ Diagnostic Process for Suspected Skin Cancer: Observational Pilot Study
Bibliographic record
Abstract
Background: Skin cancers are the most frequent types of cancer, and the incidence continues to rise. Teledermoscopy is a promising tool in the diagnostic process of potential skin cancer, and new technologies are constantly being developed. However, little information is available on how teledermoscopy affects physicians' time consumption. Objective: This study aimed to investigate whether teledermoscopy can shorten the diagnostic process for physicians examining skin lesions suspected of skin cancer. Methods: We recorded the time primary care providers, dermatologists, plastic surgeons, and pathologists spent examining lesions suspected of skin cancer, with and without teledermoscopy. Furthermore, we looked at five different diagnostic pathways, which reflected the most common ways through the Danish health care system for patients with suspected skin cancer, to estimate the total amount of time physicians spent examining these lesions with and without teledermoscopy. Results: A total of 118 time recordings were obtained. With teledermoscopy, the diagnostic process was significantly shortened for dermatologists (P=.008) but prolonged for primary care providers (P=.03). While the use of teledermoscopy saved time in one of the diagnostic pathways, it increased the time spent in the four others. Conclusions: Our research suggests that the implementation of teledermoscopy could save time for dermatologists and potentially plastic surgeons and pathologists, provided that a sufficient number of benign skin lesions can be accurately diagnosed and excluded from further examination and treatment. In contrast, the implementation of teledermoscopy might prolong primary care providers' consultation time.
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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 | 0.000 | 0.000 |
| 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".