MedElevator Войти в исследования
← Поиск публикаций

DOI 10.1155/2022/9170274

Медицинская библиотека · Computational and mathematical methods in medicine · 2022

Three-Dimensional Ultrasound Images in the Assessment of Bladder Tumor Health Monitoring under Deep Learning Algorithms.

Shao Changhua, Sun Aichun, Xue Hanwen, Di Xianqiang

СтатьяРандомизированное исследованиеОтозванная публикацияПеревод пока не подготовлен
Источник пометил публикацию как отозванную.

Аннотация

This study was aimed at exploring the application value of three-dimensional (3D) ultrasound based on deep learning and continued nursing health monitoring (CNHM) mode in promoting the recovery of bladder cancer patients after surgery. 60 patients who underwent muscular noninvasive superficial bladder cancer and bladder perfusion treatment were selected as the research objects. The patients were randomly divided into two groups: an experimental group (30 cases) and a control group (30 cases). Patients in the experimental group adopted a CNHM model during the bladder perfusion treatment. The patients in control group adopted ordinary health monitoring mode. All patients underwent 3D ultrasound examination, and all images were processed using the convolutional neural network (CNN) algorithm. All patients were followed up regularly within 12 after the treatment. The imaging data, quality of life, satisfaction, and complications of the two groups of patients were compared in each time period. The ultrasound image processed by the CNN algorithm was clearer than that processed by the original method, showing higher image quality and more prominent lesion features. After 12 months of health monitoring intervention, the overall health status, scores of various functional areas, and score of functional subscales of the experimental group were greatly higher than those of the control group, and the differences were statistically significant (P < 0.05). The incidence of adverse reactions in the experimental group was much lower than that in the control group, and the difference was statistically obvious (P < 0.05). The comparison of the recurrence rate between the two groups of patients in each time period was statistically significant. The satisfaction score of the experimental group was much higher than the score of the control group, showing statistically significant difference (P < 0.05). CNN algorithm showed high application value in 3D ultrasound image processing, and the CNHM model was very beneficial to the postoperative recovery of bladder cancer patients.

Для цитирования: Shao Changhua, Sun Aichun, Xue Hanwen, Di Xianqiang. Three-Dimensional Ultrasound Images in the Assessment of Bladder Tumor Health Monitoring under Deep Learning Algorithms.. Computational and mathematical methods in medicine. 2022. DOI: 10.1155/2022/9170274.

Предметные рубрики MeSH

Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.