Ultrasound Image under Artificial Intelligence Algorithm to Evaluate the Intervention Effect of Accelerated Rehabilitation Surgery Nursing on Laparoscopic Hysterectomy

Yu, Haiwei; Zhao, Ziming; Duan, Xiuping; Zhou, Jian; Su, Dechun

doi:10.1155/2022/9042954

Cited by 3 publications

(3 citation statements)

References 26 publications

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“…However, this procedure also has significant disadvantages and is prone to post-operative complications such as incisional hernia and intestinal canal damage [11,12]. This study found that the study group experienced fewer hospitalization days and a lower frequency of post-operative complications than the control group, similar to the research by Li et al [7] and Yu et al [13]. These investigations revealed that under the nursing intervention model, the psychological, physical, and social care needs of elderly patients can be met, with patients' disease perceptions and their psychological status improving.…”

Section: Discussionsupporting

confidence: 87%

Evaluation on the efficacy of nursing intervention based on the self-efficacy theory model in elderly patients undergoing total laparoscopic hysterectomy

2023

European Journal of Gynaecological Oncology

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The effectiveness of nursing interventions based on the self-efficacy in elderly patients receiving total laparoscopic hysterectomy was assessed. 100 senior patients undergoing total laparoscopic hysterectomy were committed to our hospital from January 2020 to February 2021. Patients were randomized into the study group (n = 51) and control group (n = 49), according to the time of surgery. The control group was given a conventional care plan, while the study group was given conventional care plus a nurse intervention based on a self-efficacy plan. The total post-operative disease uncertainty scores were relatively lower than before surgery both in the control group and the study group (p < 0.05). In particular, the disease uncertainty scale in the post-operative group was reduced in the study group as compared to that in the control group (p < 0.05). The post-operative self-efficacy scale scores of patients in the control group and the study group were increased than that in the pre-operative patients (p < 0.05). In particular, the post-operative self-efficacy scale scores of patients in the study group were higher than that in the control group. Patients in the study group had a lower incidence of post-operative complications than that in the control group. After one year of follow-up, the overall Pelvic Floor Distress Inventory-20 (PFDI-20) scores at 3 months and 12 months were statistically significant higher than pre-operative scores (p < 0.05). In particular, the post-operative patients’ pelvic floor function in the study group were lower than that in the control group. It seems that a self-efficacy-based nursing intervention program applied to elderly patients after laparoscopic total hysterectomy was effective in improving patients’ disease uncertainty and self-efficacy, shortening the length of hospital stay and reducing the incidence of postoperative complications, with little impact on pelvic floor function.

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Section: Discussionsupporting

confidence: 87%

Evaluation on the efficacy of nursing intervention based on the self-efficacy theory model in elderly patients undergoing total laparoscopic hysterectomy

2023

European Journal of Gynaecological Oncology

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“…Ultrasonic technique of the BCNN model based on deep learning is accurate for evaluating pelvic floor function. Yu et al [ 27 ] evaluated the effect of laparoscopic hysterectomy based on artificial intelligence imaging; ultrasound imaging based on ISCB algorithm can high-quality display the pelvic floor structure of patients undergoing total laparoscopic hysterectomy, improve the diagnostic rate of doctors, accelerate postoperative rehabilitation of patients, reduce postoperative pain, and improve patient satisfaction. In this experiment, BCNN-S had the highest accuracy of 88.98%; BCNN-R had the highest recall of 88.51%; and BCNN-R had the highest precision of 97.34%.…”

Section: Discussionmentioning

confidence: 99%

Ultrasound Evaluation of Pelvic Floor Function after Transumbilical Laparoscopic Single-Site Total Hysterectomy Using Deep Learning Algorithm

Zhu

Zhang

et al. 2022

Computational and Mathematical Methods in Medicine

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This study was aimed at investigating the ultrasound based on deep learning algorithm to evaluate the rehabilitation effect of transumbilical laparoscopic single-site total hysterectomy on pelvic floor function in patients. The bilinear convolutional neural network (BCNN) structure was constructed in the ultrasound imaging system. The spatial transformer network (STN) was used to preserve image information. Two algorithms, BCNN-R and BCNN-S, were proposed to remove sensitive information after ultrasonic image processing, and then, subtle features of the image were identified and classified. 80 patients undergoing transumbilical laparoscopic single-site total hysterectomy in hospital were randomly divided into a control group and a treatment group, with 40 cases in each group. In the control group, conventional ultrasound was used to assess the image of pelvic floor function in patients undergoing laparoendoscopic single-site surgery (LESS); in the observation group, ultrasound based on deep learning algorithm was used. The postoperative incision pain score, average postoperative anus exhaust time, average hospital stay, and postoperative satisfaction of the two groups were evaluated, respectively. The highest accuracy of constructed network BCNN-S was 88.98%; the highest recall rate of BCNN-R was 88.51%; the highest accuracy rate of BCNN-R was 97.34%. The operation time, intraoperative blood loss, and exhaust time were similar between the two groups, and the difference had no statistical significance ( P > 0.05 ). The numerical rating scale (NRS) scores were compared, the observation group had less pain, the difference between the two groups had statistical significance ( P < 0.05 ), and the postoperative recovery was good. The BCNN based on deep learning can realize the imaging of the uterus by ultrasound and realize the evaluation of pelvic floor function, and the probability of pelvic floor dysfunction is small, which is worthy of clinical promotion.

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“…Among these methods, BCN-S had the highest accuracy of 88.98%, BCN-R had the highest recall rate of 88.51%, and BCN-R had the highest precision of 97.34%. Yin [32] et al showed that the pelvic floor mid-sagittal plane images processed by the artificial intelligence algorithm were clearerL the focus was more prominent, and the image quality was significantly improved. The Dice coefficient, positive predictive value, sensitivity, and Hausdorff distance of the algorithm were better than those of traditional algorithms.…”

Section: Advances In the Study Of Ai In Automated Aop Measurementmentioning

confidence: 99%

Advanced Application of Artificial Intelligence for Pelvic Floor Ultrasound in Diagnosis and Treatment

Qu¹,

Zhang²

2023

Advanced Ultrasound in Diagnosis and Therapy

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Artificial intelligence-based pelvic floor ultrasound helps the diagnosis, preoperative assessment, and postoperative monitoring of female pelvic floor dysfunction (FPFD). The application of artificial intelligence in pelvic floor ultrasound mainly includes automatic segmentation and measurement, the diagnosis of muscle injury, childbirth prediction and postoperational evaluation. It can not only overcome the problem of operator experience dependence but also improve work efficiency and simplify the workflow, which has popularized the application of pelvic floor ultrasound. However, most of the current research is still limited to the automatic segmentation of three-dimensional axial plane levator hiatus (LH). The automatic reconstruction, real-time tracking of 3D/4D images and the imaging navigation of pelvic floor surgery remain major challenges for researchers.

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Ultrasound Image under Artificial Intelligence Algorithm to Evaluate the Intervention Effect of Accelerated Rehabilitation Surgery Nursing on Laparoscopic Hysterectomy

Cited by 3 publications

References 26 publications

Evaluation on the efficacy of nursing intervention based on the self-efficacy theory model in elderly patients undergoing total laparoscopic hysterectomy

Evaluation on the efficacy of nursing intervention based on the self-efficacy theory model in elderly patients undergoing total laparoscopic hysterectomy

Ultrasound Evaluation of Pelvic Floor Function after Transumbilical Laparoscopic Single-Site Total Hysterectomy Using Deep Learning Algorithm

Advanced Application of Artificial Intelligence for Pelvic Floor Ultrasound in Diagnosis and Treatment

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