ArticleJournal of medical systems2015
The current and future needs of our medical systems.
Article in Journal of medical systems, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Mobile Applications for Type 2 Diabetes Risk Estimation: a Systematic Review.Journal of medical systems · 2015Pooled it
- A Mobile Post Anesthesia Care Unit Order Reminder System Improves Timely Order Entry.Journal of medical systems · 2024Article
- Combining the ASA Physical Classification System and Continuous Intraoperative Surgical Apgar Score Measurement in Predicting Postoperative Risk.Journal of medical systems · 2015Article
- An electronic medical record system with treatment recommendations based on patient similarity.Journal of medical systems · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As another publishing year come to a close at the Journal of Medical Systems, it is clear that as a scientific community, the need for a more detailed understanding of the impact of medical systems has never been greater. Technologies that were emerging just a short time ago including radio frequency identification (RFID), wireless body area networks (WBAN), and telecare medicine information systems (TMIS) are now ubiquitous. Additionally, closed-loop controller systems have gained regulatory approval in many settings. As the complexity of these medical systems grow, so to do the challenges of ensuring we have secure, efficient, and reliable systems that integrate into our clinical workflows.
Indexed as
Identifiers
25638720What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.