Bibliographic record
Abstract
Background and Aim : Electronic health record is one of the most important achievements of the eHealth to achieve a patient-centered care. The aim of the patient-centered care is accessibility of all patient to clinicians to have the best decisions for the patients. Creating an environment for sharing and developing e-health caused the security and privacy of health of patients to become an important and challenging issue. In this regard, it is necessary to healthcare organizations to create the security solution in order to protect the rights of their patients. Materials and Methods : This review is based on the library research and Internet searches in the major databases such as Web of science, Emerald, Proquest, EBSCO host research, PubMed and search engines like Google and Google Scholar. In this review, essays, books in the field of medical informatics and security of systems in the health system have been studied. Ethical Considerations : Publication of the results is carried out without bias, honestly and by citing the original reliable resources and references. Findings : In this review, how to maintain security programs and health systems in addition to improving quality of care to achieve three main objectives related to security, including confidentiality, accuracy, and the availability around three core axes of administrative safeguards, physical safeguards, and technical safeguards are discussed. Conclusion : The health centers should be consistent in four main areas standards, rules and policies related to the contribution and access to information, communications and operations management, access control and security of human resources including awareness and education of the users about security issues should involve a range of users ranging from therapists to legal and technical experts and always consider the principle of protecting the rights of patients with convenient access to patient information in order to develop their own security and development of programs. Citation : Karami M. Patient's Information Rights: Strategies for Information Security in the Electronic Environment. Bioeth Health Law J. 2017; 1(2):9-12.
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 | 0.009 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.050 | 0.015 |
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".