Feasibility study of using statistical process control to optimize quality assurance in radiotherapy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose The purpose of this paper is to evaluate and improve the quality and the reliability of pre‐treatment quality controls of an efficient technique of radiotherapy called IMRT (intensity‐modulated radiation therapy). The aim is then to determine if the controls can be safely reduced while keeping an optimal level of quality. Design/methodology/approach The statistical process control method (SPC) was applied to quality assurance in IMRT. In order to characterize prostate and head‐and‐neck treatment process variability, individual value control charts and moving‐range control charts were established. Findings Control charts showed that prostate and head‐and‐neck treatment processes are only subject to random causes of variability, which means they are statistically controlled. It was proved that both processes are statistically stable and capable. Originality/value The paper shows that SPC is an efficient method to objectively determine if quality controls can be reduced.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it