ArticleComputational intelligence and neuroscience2022
Ultrasound Image under Artificial Intelligence Algorithm to Evaluate the Intervention Effect of Accelerated Rehabilitation Surgery Nursing on Laparoscopic Hysterectomy.
Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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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.
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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.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.
- Enhanced recovery after surgery reduces postoperative nausea and vomiting in gynecological surgery: systematic review and meta-analysis of randomized and observational studies.Frontiers in medicine · 2026Pooled it
- Ultrasound Evaluation of Pelvic Floor Function after Transumbilical Laparoscopic Single-Site Total Hysterectomy Using Deep Learning Algorithm.Computational and mathematical methods in medicine · 2022Trial
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To explore the application value of accelerated rehabilitation surgery (ERAS) nursing in laparoscopic total hysterectomy, 120 patients who underwent laparoscopic total hysterectomy for benign uterine diseases in the hospital were selected as the research object. According to different nursing schemes, they were divided into 60 cases in the experimental group (ERAS nursing program) and 60 cases in the control group (traditional perioperative nursing). All patients underwent postoperative ultrasonography, and the intraoperative and postoperative rehabilitation indexes of the two groups were analyzed. Moreover, an improved standard Capon beamforming (ISCB) algorithm is proposed, which is compared with SCB algorithm, sequential regression algorithm (SER), and recursive least square (RLS) algorithm. The results showed that the center average power and background average power (-46.92, -33.85) of the ISCB algorithm were significantly lower than those of SCB algorithm (-36.18, -23.64), SER algorithm (-39.02, -27.31), and RLS algorithm (-34.88, -24.66), while the contrast and resolution (19.11, 15.57) were significantly higher than those of SCB algorithm (12.74, 9.01), SER algorithm (13.86, 7.89), and RLS algorithm (13.26, 8.26) (
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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.