Past, present, and future perspectives of telemedical assistance at sea: a systematic review
Bibliographic record
Abstract
BACKGROUND: Telemedicine is an effective technology for evaluating, diagnosing, treating, and providing health care services for remote populations, including seafarers, in case of diseases or accidents on board. Delivery of telemedicine in a maritime environment is not an easy task and, in general, differs from what can be done onshore. The aim of this review is to provides an overview of Telemedical Maritime Assistance Services (TMAS) in Europe by describing the previous and current status in terms of communication technologies as well as the nature of services rendered at sea. Secondly, to discuss the areas needing improvement and future directions to improve the quality of offshore telemedicine services. MATERIALS AND METHODS: Different databases, including PubMed (Medline), Google Scholar, Scopus, and journal of International Maritime Health, were searched between August 1 and September 15, 2019. Articles only published from 1969 to 2019 were considered. Relevant articles were selected by reviewing keywords, titles, and abstracts initially based on our inclusion and exclusion criteria. We critically reviewed the full-text articles included in this review. Information on the means of communication, telemedicine services, years of publication, and the name of the first author was extracted from selected studies. The quality of the selected studies was assessed using the criteria of the Newcastle-Ottawa scale. RESULTS: Initially, 135 articles were identified through searching various databases by using keywords, abstracts, and titles. After removing the duplicates, 121 articles remained. Then we performed an independent article assessment and selection based on the selection criteria, which removed an additional 61 studies, leaving 60 papers. Finally, 27 full-text papers left, and we critically reviewed it. In 27 accepted articles, email and telephone were used most often and accounted for 30% (17/57) and 28% (16/57) of all communication links, respectively. Teleconsultation was the most used telemedicine service on board and represented 58.6% (17/29) of accepted papers. CONCLUSIONS: Email and telephone were the principal means of TMAS doctors to provide medical advice as well as assistance for patients at sea. Despite the potential offered by technological progress, there are still many limitations to the provision of adequate medical care at sea. The modernisation of telemedicine services will help decrease the gap in healthcare delivery at sea.
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 | 0.012 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.018 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".