Establishment of a remote diagnostic histopathology service using whole slide imaging (digital pathology)
Bibliographic record
Abstract
BACKGROUND: Whole slide imaging (WSI) has diverse applications in modern pathology practice, including providing histopathology services to remote locations. MATERIALS AND METHODS: Utilising an existing contractual partnership with a Northern Ontario group of hospitals, the feasibility of using WSI for primary diagnostic services from Toronto was explored by the dedicated working group. All aspects explored from information technology (IT), laboratory information system (LIS) integration, scanning needs, laboratory workflow and pathologist needs and training, were taken into account in the developing the rationale and business case. RESULTS: The financial outlay for a scanner was $CA180K (approximately £105.6 k) after discounts. There were no human resource requirements as staff were reorganised to cater for slide scanning. Additional IT/LIS costs were not incurred as existing connectivity was adapted to allow two site groups (gastrointestinal and skin) to pilot this study. Scanned slides were available for pathologist review 24-96 hours sooner than glass slides; there was a 2-day improvement for final authorised cases, and per annum savings were: $CA26 000 (£15.2 k) in courier costs, $CA60 000 (£35.2 k) travel and $CA45 000 (£26.4 k) in accommodation, meals and car rental expense. CONCLUSION: WSI is a viable solution to provide timely, high-quality and cost efficient histopathology services to underserviced, remote areas.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".