Ultrasound Image Quality Comparison Between a Handheld Ultrasound Transducer and Mid-Range Ultrasound Machine
Why this work is in the frame
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Bibliographic record
Abstract
Objectives: Not all labor and delivery floors are equipped with ultrasound machines which can serve the needs of both obstetricians and anesthesiologists. This cross-sectional, blinded, randomized observational study compares the image resolution (RES), detail (DET), and quality (IQ) acquired by a handheld ultrasound, the Butterfly iQ, and a mid-range mobile device, the Sonosite M-turbo US (SU), to evaluate their use as a shared resource. Methods: Seventy-four pairs of ultrasound images were obtained for different imaging purposes: 29 for spine (Sp), 15 for transversus abdominis plane (TAP) and 30 for diagnostic obstetrics (OB) purposes. Each location was scanned by both the handheld and mid-range machine, resulting in 148 images. The images were graded by three blinded experienced sonographers on a 10-point Likert scale. Results: The mean difference for Sp imaging favored the handheld device (RES: -0.6 [(95% CI -1.1, -0.1), p = 0.017], DET: -0.8 [(95% CI -1.2, -0.3), p = 0.001] and IQ: -0.9 [95% CI-1.3, -0.4, p = 0.001]). For the TAP images, there was no statistical difference in RES or IQ, but DET was favored in the handheld device (-0.8 [(95% CI-1.2, -0.5), p < 0.001]). For OB images, the SU was favored over the handheld device with RES, DET and IQ with mean differences of 1.7 [(95% CI 1.2, 2.1), p < 0.001], 1.6 [(95% CI 1.2, 2.0], p < 0.001] and 1.1 [(95% CI 0.7, 1.5]), p < 0.001), respectively. Conclusions: Where resources are limited, a handheld ultrasound may be considered as a potential low-cost alternative to a more expensive ultrasound machine for point of care ultrasonography, better suited to anesthetic vs. diagnostic obstetrical indications.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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 it