Healing From a Distance: A Cross-sectional Study on the Diagnostic Reliability of Store-and-Forward Teledermatology
Bibliographic record
Abstract
Background Telemedicine delivers health care services between two distant locations through the use of information and communication technology. Several medical specializations, such as dermatology, have incorporated telemedicine into their practice. Since dermatologists are trained to diagnose skin, hair, and nail conditions with a clinical eye, teledermatology may be an alternative when a traditional face-to-face clinic visit is not feasible. Objective The purpose of this study was to evaluate the diagnostic reliability of teledermatology. Methods A cross-sectional study was conducted among patients from 2 government hospitals. A total of 39 patients were seen in a face-to-face setting and diagnosed by a consultant dermatologist. A written history of their present illness and accompanying photographs were taken and were shown to 3 consultant teledermatologists, who then diagnosed their condition. Two senior dermatology residents then rated the face-to-face and teledermatology diagnoses as either complete agreement, partial agreement, or no agreement. Descriptive statistics was used to summarize the general and clinical characteristics of the participants. The Cohen kappa was used to assess agreement in the evaluations between the teledermatology and face-to-face diagnoses by senior resident raters #1 and #2. Results Over 70% of the diagnoses were deemed as either partial or in complete agreement with the face-to-face diagnosis for senior resident rater #1. Similarly, over 80% of the diagnoses were deemed as either partial or in complete agreement with the face-to-face diagnosis for senior resident rater #2. The agreement between the ratings of senior residents #1 and #2 ranged from fair to substantial. Conclusions The findings of the study showed that the diagnostic concordance of in-person clinicians and teledermatologists ranges from fair to substantial, with over 70% of the diagnoses in partial or complete agreement. Although face-to-face consultations remain the gold standard, teledermatology is an important alternative where dermatologic care is not accessible. Conflicts of Interest None declared.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".