ReviewCureus2024
Mapping Research Trends and Collaborative Networks in Swarm Intelligence for Healthcare Through Visualization.
Review in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Swarm intelligence, evolved from the self-organized behavior of social insects, has become an essential method under artificial intelligence for handling complex and dynamic issues. This study visualizes and analyzes the use of swarm intelligence in healthcare, focusing on its role in managing rising medical data complexity, optimizing diagnostic and therapeutic solutions, and supporting personalized healthcare. The analysis, based on literature from Scopus (2003-2024) using Biblioshiny and VOSviewer, reveals a strong increase in publications since 2017, with central themes around disease diagnosis, treatment optimization, medical image analysis, and real-time patient monitoring through frameworks like the Internet of Medical Things (IoMT) and swarm learning. Key findings include the identification of prolific authors, influential journals, and significant collaborative networks, with China and India emerging as major contributors. These insights underscore the multidisciplinary nature of swarm intelligence in healthcare, positioning it as a potential game-changer in medical diagnostics and patient care through collaborative and innovative research.
Indexed as
Identifiers
What 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.