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Impact of Chronic Adenoid Hypertrophy on Quality of Life Index in Children and Role of Adenoidectomy. 慢性腺样体肥大对儿童生活质量指数的影响及腺样体切除术的作用。
IF 0.6 Q4 ENGINEERING, BIOMEDICAL
International Journal of Biomedical Engineering and Technology
Pub Date : 2023-12-01 Epub Date: 2023-06-24 DOI: 10.1007/s12070-023-04000-z
Deepa Shivnani, Mallikarjun R Kobal, E V Raman, M S Shruthi

Objectives: To analyze the effects of chronic adenoid hypertrophy on quality of life (QOL) of children and caregivers and compare quality of life of child before and after adenoidectomy. Materials & Methods: Prospective, observational before and after questionnaire based assessment study at a pediatric otorhinolaryngology specialty center in a metropolitan quaternary care hospital. Children aged between 2 and 12 years undergoing adenoidectomy were included. Parents were asked to fill the Obstructive Sleep Apnea-18 (OSA-18) Quality of Life Index Questionnaire one day before surgery and after one month of surgery during their scheduled follow-up visit. The study was conducted over a period of 1 year and total of 40 children's assessment was done. Results were tabulated and analyzed. Results: The mean age of presentation was 6 years. Based on OSA-18 quality of life assessment scoring the total pre-operative mean score was 73.3 and post-operative was 40.5. There was significant change in OSA-18 total score and individual domain scores post-operatively indicating significant improvement in QOL post adenoidectomy. The domains most affected due to chronic adenoid hypertrophy were physical suffering, caregiver concerns and sleep disturbance (p value < 0.001).Conclusion: Chronic adenoid hypertrophy has major impact on quality of life of a child along with caregiver concern and they show significant improvement after adenoidectomy.

Supplementary information: The online version contains supplementary material available at 10.1007/s12070-023-04000-z.

目的:分析慢性腺样体肥大对儿童及护理人员生活质量的影响，比较腺样体切除术前后儿童生活质量的差异。材料与方法:在某都市四科医院儿童耳鼻喉科专科中心进行前瞻性、观察性问卷评估前后研究。接受腺样体切除术的儿童年龄在2至12岁之间。要求家长在手术前一天和术后一个月随访期间填写阻塞性睡眠呼吸暂停-18 (OSA-18)生活质量指数问卷。这项研究进行了1年，共对40名儿童进行了评估。将结果制成表格并进行分析。结果:患者平均发病年龄6岁。根据OSA-18生活质量评分，两组患者术前平均得分为73.3分，术后平均得分为40.5分。术后OSA-18总分和个体域评分均有显著变化，表明腺样体切除术后生活质量有显著改善。慢性腺样体肥大影响最大的领域是身体痛苦、照顾者担忧和睡眠障碍(p值)。结论:慢性腺样体肥大和照顾者担忧对儿童的生活质量有重大影响，并在腺样体切除术后显著改善。补充资料:在线版本包含补充资料，网址为10.1007/s12070-023-04000-z。
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引用次数: 0
Incubator for Home-based Baby Care Using IoT 基于物联网的家庭婴儿护理孵化器
IF 1.1 Q4 ENGINEERING, BIOMEDICAL
International Journal of Biomedical Engineering and Technology
Pub Date : 2023-03-24 DOI: 10.12691/jbet-10-1-1
Amit Kumar Singh, M. Leela, R. Jeevitha, R. Mirudhularani, S. Vigneswari
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引用次数: 0
Rapid detection of COVID-19 from chest X-ray images using deep convolutional neural networks 基于深度卷积神经网络的胸部x线图像快速检测COVID-19
IF 1.1 Q4 ENGINEERING, BIOMEDICAL
International Journal of Biomedical Engineering and Technology
Pub Date : 2023-01-01 DOI: 10.1504/ijbet.2023.10053528
K. V. Kadambari, S. Panigrahi, U. Raju, Harika Ala, Debanjan Pathak
The entire world is suffering from the corona pandemic (COVID-19) since December 2019. Deep convolutional neural networks (deep CNN) can be used to develop a rapid detection system of COVID-19. Among all the existing literature, ResNet50 is showing better performance, but with three main limitations, i.e.: 1) overfitting;2) computation cost;3) loss of feature information. To overcome these problems authors have proposed four different modifications on ResNet50, naming it as LightWeightResNet50. An image dataset containing chest X-ray images of coronavirus patients and normal persons is used for evaluation. Five-fold cross-validation is applied with transfer learning. Ten different performance measures (true positive, false negative, false positive, true negative, accuracy, recall, specificity, precision, F1-score and area under curve) are used for evaluation along with fold-wise performance measures comparison. The four proposed methods have an accuracy improvement of 4%, 13%, 14% and 7% respectively when compared with ResNet50.
自2019年12月以来，全世界都在遭受冠状病毒大流行(COVID-19)的折磨。深度卷积神经网络(Deep CNN)可以用于开发COVID-19的快速检测系统。在现有的文献中，ResNet50表现出更好的性能，但主要存在三个局限性，即:1)过拟合;2)计算成本;3)特征信息丢失。为了克服这些问题，作者对ResNet50提出了四种不同的修改，将其命名为LightWeightResNet50。使用包含冠状病毒患者和正常人胸部x射线图像的图像数据集进行评估。五重交叉验证应用于迁移学习。采用10种不同的性能指标(真阳性、假阴性、假阳性、真阴性、准确性、召回率、特异性、精密度、f1评分和曲线下面积)进行评估，并对各指标进行比较。与ResNet50相比，这四种方法的准确率分别提高了4%、13%、14%和7%。
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引用次数: 0
A review on wheelchair and add-in devices design for the disabled 残疾人轮椅及辅助装置设计综述
IF 1.1 Q4 ENGINEERING, BIOMEDICAL
International Journal of Biomedical Engineering and Technology
Pub Date : 2023-01-01 DOI: 10.1504/ijbet.2023.10053530
Sateesh Reddy Avutu, Sudip Paul, B. V. Reddy
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引用次数: 2
Using artificial intelligence to design healthcare system in IoT 利用人工智能设计物联网医疗保健系统
IF 1.1 Q4 ENGINEERING, BIOMEDICAL
International Journal of Biomedical Engineering and Technology
Pub Date : 2023-01-01 DOI: 10.1504/ijbet.2023.10054053
Shipu Jin N.A.
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引用次数: 0
Evaluation of chondrocyte culture in novel airlift bioreactor using computational fluid dynamics tools 利用计算流体动力学工具评价新型气升式生物反应器中软骨细胞培养
IF 1.1 Q4 ENGINEERING, BIOMEDICAL
International Journal of Biomedical Engineering and Technology
Pub Date : 2023-01-01 DOI: 10.1504/ijbet.2023.10054325
Aditya Anand, S. Mallick, I. Chandel, B. Singh, P. Srivastava
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引用次数: 0
MRI Segmentation Using Deep Learning Network for Brain Tumor Detection 基于深度学习网络的MRI分割用于脑肿瘤检测
IF 1.1 Q4 ENGINEERING, BIOMEDICAL
International Journal of Biomedical Engineering and Technology
Pub Date : 2023-01-01 DOI: 10.1504/ijbet.2023.10054461
Ambily N, S. K
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引用次数: 0
An advanced wavelet decomposition based denoising technique for de-speckling of all ultrasound images 一种基于小波分解的超声图像去噪技术
IF 1.1 Q4 ENGINEERING, BIOMEDICAL
International Journal of Biomedical Engineering and Technology
Pub Date : 2023-01-01 DOI: 10.1504/ijbet.2023.10054699
Neetu Sood, I. Saini, Mayank Singh
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引用次数: 0
Design of artificial pancreas based on HGAPSO-FOPID control algorithm 基于HGAPSO-FOPID控制算法的人工胰腺设计
IF 1.1 Q4 ENGINEERING, BIOMEDICAL
International Journal of Biomedical Engineering and Technology
Pub Date : 2023-01-01 DOI: 10.1504/ijbet.2023.10057981
Anuja Nanda, A. Patra
{"title":"Design of artificial pancreas based on HGAPSO-FOPID control algorithm","authors":"Anuja Nanda, A. Patra","doi":"10.1504/ijbet.2023.10057981","DOIUrl":"https://doi.org/10.1504/ijbet.2023.10057981","url":null,"abstract":"","PeriodicalId":51752,"journal":{"name":"International Journal of Biomedical Engineering and Technology","volume":"1 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66807674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Atherosclerotic Plaque Segmentation Using Modified UNet with Hybrid Pooling Layers 基于混合池化层的改进UNet分割动脉粥样硬化斑块
IF 1.1 Q4 ENGINEERING, BIOMEDICAL
International Journal of Biomedical Engineering and Technology
Pub Date : 2023-01-01 DOI: 10.1504/ijbet.2023.10057116
M. Pohit, Neeraj Sharma, Pankaj K Jain, Soni Singh
{"title":"Atherosclerotic Plaque Segmentation Using Modified UNet with Hybrid Pooling Layers","authors":"M. Pohit, Neeraj Sharma, Pankaj K Jain, Soni Singh","doi":"10.1504/ijbet.2023.10057116","DOIUrl":"https://doi.org/10.1504/ijbet.2023.10057116","url":null,"abstract":"","PeriodicalId":51752,"journal":{"name":"International Journal of Biomedical Engineering and Technology","volume":"64 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66807982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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