Evaluation of functional magnetic resonance imaging under artificial intelligence algorithm on plan-do-check-action home nursing for patients with diabetic nephropathy
Open accessAbstract
This study aimed to evaluate the effect of functional magnetic resonance imaging (fMRI) under the fuzzy C‐means (FCM) clustering algorithm on plan‐do‐check‐action (PDCA) home nursing for patients with diabetic nephropathy (DN). As the characteristics of fMRI image data were combined, the FCM algorithm was improved and applied into the clustering processing of fMRI activation regions of patients. 64 patients with DN were chosen as the research objects and were divided into the research group with PDCA home nursing and the control group with routine home nursing. The patients were randomly divided into the research group (n = 32) and the control group (n = 32). The curative effect, nursing satisfaction, and quality of life of patients after nursing were compared. The results showed that the coverage of fMRI activation points was significantly higher as being detected by the FCM algorithm, and the running time was shortened by 33.6 min. After nursing, the total effective rates in the research group and the control group were 87.5% vs. 34.4% in 3 months, 93.8% vs. 68.8% in 6 months, and 96.9% vs. 75.0% in 12 months, respectively; those in the research group were significantly higher than those in the control group (P < 0.05). The nursing satisfaction score (91.3 ± 4.5 vs. 80.9 ± 5.2) and nursing service quality score (89.7 ± 6.6 vs. 80.3 ± 7.1) in the research group were also significantly higher than those in the control group (P < 0.05). Meanwhile, the scores of each item after nursing in the research group were significantly higher than those in the control group (P < 0.05). The improved FCM algorithm detected the activation regions in the fMRI images more effectively, which could provide help for diagnosis and reduce error and misdiagnosis. At the same time, the PDCA home nursing also offered great help to the recovery of patients with DN, which was more superior for the curative effect of hospitalization, the promotion of recovery, and the improvement of patients’ quality of life.
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Du et al. (41) implemented an AI-based Plan-Do-Check-Action (PDCA) home nursing model for patients with diabetic nephropathy, which led to significant improvements in clinical effectiveness and patient satisfaction over 12 months.
“Du et al. (41) implemented an AI-based Plan-Do-Check-Action (PDCA) home nursing model for patients with diabetic nephropathy, which led to significant improvements in clinical effectiveness and patient satisfaction over 12 months by enabling dynamic adjustments to care plans based on AI-generated insights.”
From Artificial intelligence in nursing: an integrative review of clinical and operational impacts (2025) · cites this paper as [41]
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- Authors
- Du, Q., Liang, D., Zhang, L., Chen, G., & Li, X.
- Corresponding author
- Du, Qianqian
- Venue
- Contrast Media & Molecular Imaging
- Publisher
- Wiley
- Published
- 2022-01
- Volume
- 2022
- Issue
- 1
- Pages
- 9882532-9882532
- ISSN
- 1555-4309 (ISSN-L)
- 1555-4317
- PMC
- PMC8975661
- OpenAlex
- W4220761207
- Cited by
- 13
- References
- 18
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 3 · 2023: 2 · 2022: 1
- FWCI
- 0.90
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Contrast Media & Molecular Imaging (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Hebei Youth Science and technology project (20160768)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Health Sciences › Medicine › Nephrology › Chronic Kidney Disease and Diabetes
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Keywords
- diabetic nephropathy, home care nursing, Plan-Do-Check-Act cycle, fuzzy c-means clustering, functional MRI, nursing satisfaction, quality of life, nursing service quality
- MeSH terms
- Algorithms, Artificial Intelligence, Diabetes Mellitus, Diabetic Nephropathies, Home Nursing, Humans, Magnetic Resonance Imaging, Quality of Life
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