Trial reportContrast media & molecular imaging2022
Evaluation of Nursing Effects of Pelvic Floor Muscle Rehabilitation Exercise on Gastrointestinal Tract Rectal Cancer Patients Receiving Anus-preserving Operation by Intelligent Algorithm-based Magnetic Resonance Imaging.
Trial report in Contrast media & molecular imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06461234 (Establishment of an Artificial Intelligence Multidimensional Early Warning Diagnostic and Prognostic Model of Pelvic Floor Rehabilitation Therapy in the Chinese Population), which is not on this map. Cited by 9 papers, 3 of them syntheses 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.
Establishment of an Artificial Intelligence Multidimensional Early Warning Diagnostic and Prognostic Model of Pelvic Floor Rehabilitation Therapy in the Chinese Population: a Prospective Cohort Study.
Who cites it
9 citing papers in PubMed, 3 syntheses or guidelines pooled it, 12 citations in OpenAlex.
- Artificial Intelligence Supported Analysis of Anal Sphincter and Levator Ani Muscle Using Medical Imaging Techniques: A Systematic Review.International urogynecology journal · 2026Pooled it
- Integrative review of artificial intelligence applications in nursing: education, clinical practice, workload management, and professional perceptions.Frontiers in public health · 2025Pooled it
- Current Status and Role of Artificial Intelligence in Anorectal Diseases and Pelvic Floor Disorders.JSLS : Journal of the Society of Laparoendoscopic SurgeonsPooled it
- Effect of 3D Animation Combined with Teach-Back Health Education on Pelvic Floor Muscle Training in LARS Patients: A Randomized Controlled Trial.Journal of nursing management · 2023Trial
- Enhanced recovery after surgery pathways and postoperative gastrointestinal function in colorectal cancer: A prospective cohort study.World journal of gastrointestinal surgery · 2026Article
- Artificial intelligence-driven gastrointestinal functional assessment: multimodal imaging, digital biomarkers, and real-time monitoring.Frontiers in physiology · 2026Review
- Artificial intelligence in nursing: an integrative review of clinical and operational impacts.Frontiers in digital health · 2025Review
- Review
- Micro video incentive nursing intervention improves the psychological state and quality of life in patients with rectal cancer after enterostomy.American journal of translational research · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Based on magnetic resonance imaging (MRI) technology under artificial intelligence algorithm, the postoperative nursing effects of pelvic floor muscle rehabilitation exercise on gastrointestinal tract rectal cancer (RC) patients were investigated. A total of 88 patients receiving RC anus-preserving surgery in hospital were selected. The included patients were divided randomly into the experimental group (44 cases) and the control group (44 cases). Patients in the control group engaged in Kegel motion, while patients in the experimental group underwent self-designed comprehensive pelvic floor training. Anorectum function rating scale and quality of life questionnaire for colorectal cancer (EORTC QLQ-CR29) were utilized to compare and analyze anus functions and living quality of patients in the two groups. Besides, all patients in two groups received MRI examinations, and images were processed by a convolutional neural network (CNN) algorithm. The results showed that in MRI images, there were significant signal differences between lesion tissues and normal tissues. After being processed by an artificial intelligence algorithm, the definition of MRI images was remarkably enhanced with clearer lesion edges. The quality of images was also significantly improved. Besides, the comparison of anus functions of patients in two groups showed that the differences demonstrated statistical meaning after the intervention (
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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.