Bibliographic record
Abstract
Introduction Picture Archiving and Communication System (PACS) is a medical imaging technology which provides safe storage and convenient access to images from multiple modalities. The greatest impact of PACS has been on the Radiology Department of the hospital. It helps to access and deliver images and related data timely and in a very efficient way. It has proven very effective tool in eliminating barriers of film based radiology. It has removed various gaps in providing services to patients and thus has smoothened the functioning of various activities related to patient care delivery in the hospital. Aims and objectives In this study we would try to bring various factors related to its implementation and benefits it could bring to the health facility regarding various functioning activities and impact on work practices and the user acceptance of PACS within and outside the hospital. Methodology A review of literature from various studies was done. Sites used in search are Pubmed, Google scholarly articles, proquest and various National and International Journals. Results In a study done to assess the impact of the introduction of a picture-archiving and communication system (PACS) on the adult intensive care unit (AICU) at the Royal Brompton NHS Trust in London it was found that time required to obtain an image reduced from 90 to 60 minutes alongside reduction of workload on radiographers. In another study done at a large tertiary care hospital in Canada it was found that the users namely radiologists, technologists and clinicians were highly satisfied with the perceived benefits of the PACS. In the study on the acceptance of work practice changes six months after the introduction of a picture archiving and communication system (PACS) in New South Wales results showed that the PACS had received a high level of acceptance. The respondents would not like to return to a film-based practice. They were happy with the accessibility of images, especially when patients returned from an X-ray examination.
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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 | 0.003 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.001 |
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".