ReviewZhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery2023
[Application and research progress of artificial intelligence technology in trauma treatment].
Review in Zhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery, 2023. 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, 2 citations in OpenAlex.
- Rapid trauma classification under data scarcity: an emergency on-scene decision model combining natural language processing and machine learning.Medical & biological engineering & computing · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To review the application and research progress of artificial intelligence (AI) technology in trauma treatment. Methods: The recent research literature on the application of AI and related technologies in trauma treatment was reviewed and summarized in terms of prehospital assistance, in-hospital emergency care, and post-traumatic stress disorder risk regression prediction, meanwhile, the development trend of AI technology in trauma treatment were outlooked. Results: The AI technology can rapidly analyze and manage large amount of clinical data to help doctors identify patients' situation of trauma and predict the risk of possible complications more accurately. The application of AI technology in surgical assistance and robotic operations can achieve precise surgical plan and treatment, reduce surgical risks, and shorten the operation time, so as to improve the efficiency and long-term effectiveness of the trauma treatment. Conclusion: There is a promising future for the application of AI technology in the trauma treatment. However, it is still in the stage of exploration and development, and there are many difficulties of historical data bias, application condition limitations, as well as ethical and moral issues need to be solved.
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.