Radiotherapy basics for family physicians. Potent tool for symptom relief.
Bibliographic record
Abstract
OBJECTIVE: To review the use of radiotherapy in cancer care, especially the role of radiation in palliative care. QUALITY OF EVIDENCE: MEDLINE was searched from January 1966 to January 2004. Relevant articles evaluating indications for radiotherapy were reviewed. This paper describes use of radiotherapy based on well established current radiotherapy practices and level I and II evidence. MAIN MESSAGE: A substantial number of patients seeing family physicians develop cancer or die of it. Despite its effectiveness, radiotherapy remains underused in management of cancer patients. Broad uses of radiotherapy in cancer care include curative treatment, palliative symptom control, and management of oncologic emergencies. Radiotherapy can be especially effective for treating common complications of cancer, including painful bone and soft tissue metastases, hemoptysis, dyspnea, dysphagia, brain metastases, and spinal cord compression. CONCLUSION: Radiotherapy is a vital aspect of both curative and palliative cancer treatment. Understanding the basics of radiotherapy can assist family physicians in providing complete care for their cancer patients.
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.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.004 |
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".