Software for the estimation of organ equivalent and effective doses from diagnostic radiology procedures
Bibliographic record
Abstract
Diagnostic radiological imaging such as conventional radiography, fluoroscopy and computed tomography (CT) examinations will continue to provide tremendous benefits in modern healthcare. The benefit derived by the patient should far outweigh the risk associated with a properly conducted imaging examination. Nonetheless, it is very important to be able to quantify the risk associated with any radiological examination of patients, and effective dose has been considered a useful indicator of patient exposure. Quantification of the risks associated with radiological imaging is very important as such information will be helpful to physicians and their patients for comparing risks from various imaging examinations and for making informed decisions whenever there is a need for any radiological imaging. The determination of equivalent and effective doses in diagnostic radiology is of interest as a basis for estimates of risk from medical exposures. In this paper we describe a simple computer program OrgDose, which calculates the doses to 27 organs in the body and then calculates the organ equivalent and effective doses and the risk from various procedures in the radiology department including conventional radiography, fluoroscopy and computed tomography examinations. The program will be a useful tool for the medical and paramedical personnel who are involved with assessing organ and effective doses and risks from diagnostic radiology procedures.
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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 | 0.000 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 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".