A reach-out system for video microscopy analysis of ciliary motions aiding PCD diagnosis
Bibliographic record
Abstract
BACKGROUNDS: High-speed Video-Microscopy Analysis (HVMA) is now being used to aid diagnosis of Primary Ciliary Dyskinesia (PCD). Only a few centers however, are equipped with the available resources and equipment to perform these tests. We describe our experience in HVMA reaching-out to many more peripheral and relatively remote areas. A portable computer with HVMA software, video camera and a microscope were used. Fourteen disperse pediatric centers were reached and a total of 203 subjects were tested within a relatively short time (Clinical Trial Registration: NCT 01070914 (registered February 6, 2010). RESULTS: With an average time of 20 minutes per patient, the system enabled us to test approximately 10-15 subjects per day. A valid HVMA result was made in 148 subjects and helped in the diagnosis of PCD in many of the patients who were subsequently confirmed to have PCD by electron microscopy and/or immunofluoresence and/or genetics and/or nasal Nitric Oxide testing. The sensitivity of abnormal HVMA to accurately predict PCD was 90.2%. DISCUSSION AND CONCLUSION: This is the first report of an out-reach system to record HVMA for improved diagnosis of PCD in remote regions that are not within reach of PCD centers and experts. It provides immediate preliminary results and instantaneous feedback to the physician, patient and his/her family members in these areas. Future studies to compare this system to conventional desk top systems are warranted. TRIAL REGISTRATION: NCT 01070914 (registered February 6, 2010).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".