Transaction on Biomedical Engineering Applications and Healthcare最新文献_第3页

Implementation of Machine Learning (ML) in Biomedical Engineering 机器学习(ML)在生物医学工程中的应用

Transaction on Biomedical Engineering Applications and Healthcare Pub Date : 2021-04-06 DOI: 10.36647/tbeah/02.01.a004

Prof. Kshatrapal Singh, Dr.Kamal Kumar Srivastava

引用次数: 0

Advancement of the Internet Of Things (IOT) and Point Of Care (POC) in Biomedical Engineering and Healthcare 生物医学工程和医疗保健领域物联网(IOT)和护理点(POC)的发展

Transaction on Biomedical Engineering Applications and Healthcare Pub Date : 2021-04-06 DOI: 10.36647/tbeah/02.01.a003

Jeya Daisy I, Eswari P

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Amalgamation of Industry 4.0 and Healthcare within Biomedical Engineering 生物医学工程中工业4.0与医疗保健的融合

Transaction on Biomedical Engineering Applications and Healthcare Pub Date : 2021-04-06 DOI: 10.36647/tbeah/02.01.a002

S. Kalsi, V. Kakulapati

{"title":"Amalgamation of Industry 4.0 and Healthcare within Biomedical Engineering","authors":"S. Kalsi, V. Kakulapati","doi":"10.36647/tbeah/02.01.a002","DOIUrl":"https://doi.org/10.36647/tbeah/02.01.a002","url":null,"abstract":"Alternanthera brasiliana Kuntz is an important herb which is having higher medicinal properties. Through all most all of the parts are used in the traditional system of medicines. The bioactive compounds or phytochemicals present in the plant show many pharmacological activities like wound healing, anti-inflammatory, antitumor, analgesic, immunostimulant and, antimicrobial and antiviral activities. Phytochemical screening of methanolic and ethanolic extracts of, A.brasiliana leaves showed the presence of phenol and alkaloids and A.brasiliana stem extracts showed the presence of different constituents like alkaloids flavonoids steroids glycosides and saponin. The DPPH and ABTS methods were followed for studying antioxidant activities of extracts. The wound healing potential of extracts is determined by the in-vitro method by using chick embryo fibroblast cell line study revealed that both stem and leaf showing wound healing activity. From the extracts the ethanolic extracts showing great wound healing potential at a time interval. Ethanolic stem extracts show comparatively higher wound healing potency. This paves way for future studies on this plant for isolation and commercialization of phytochemicals which are responsible for wound healing property of the plant Alternanthera brasiliana Kuntz. Keyword : Alternanthera brasiliana, antioxidant, DPPH and ABTS, wound healing, MTT assay.","PeriodicalId":145122,"journal":{"name":"Transaction on Biomedical Engineering Applications and Healthcare","volume":"272 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131480462","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

Phytochemical Analysis and Biological Activities of Alternanthera Braseliana Kuntz Leaves and Stem Extracts 红花莲叶和茎提取物的植物化学分析及生物活性研究

Transaction on Biomedical Engineering Applications and Healthcare Pub Date : 2021-03-06 DOI: 10.36647/tbeah/02.01.a001

Junaidraja Ferozeraj, Muhammed Noufal M P, R. S

{"title":"Phytochemical Analysis and Biological Activities of Alternanthera Braseliana Kuntz Leaves and Stem Extracts","authors":"Junaidraja Ferozeraj, Muhammed Noufal M P, R. S","doi":"10.36647/tbeah/02.01.a001","DOIUrl":"https://doi.org/10.36647/tbeah/02.01.a001","url":null,"abstract":"Alternanthera brasiliana Kuntz is an important herb which is having higher medicinal properties. Through all most all of the parts are used in the traditional system of medicines. The bioactive compounds or phytochemicals present in the plant show many pharmacological activities like wound healing, anti-inflammatory, antitumor, analgesic, immunostimulant and, antimicrobial and antiviral activities. Phytochemical screening of methanolic and ethanolic extracts of, A.brasiliana leaves showed the presence of phenol and alkaloids and A.brasiliana stem extracts showed the presence of different constituents like alkaloids flavonoids steroids glycosides and saponin. The DPPH and ABTS methods were followed for studying antioxidant activities of extracts. The wound healing potential of extracts is determined by the in-vitro method by using chick embryo fibroblast cell line study revealed that both stem and leaf showing wound healing activity. From the extracts the ethanolic extracts showing great wound healing potential at a time interval. Ethanolic stem extracts show comparatively higher wound healing potency. This paves way for future studies on this plant for isolation and commercialization of phytochemicals which are responsible for wound healing property of the plant Alternanthera brasiliana Kuntz. Keyword : Alternanthera brasiliana, antioxidant, DPPH and ABTS, wound healing, MTT assay.","PeriodicalId":145122,"journal":{"name":"Transaction on Biomedical Engineering Applications and Healthcare","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114083983","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

Comparison of the Effect of Boiled Cotton Swabs, Alcohol Swabs and Without Swabbing on Skin Infection before an Injection 注射前水煮棉签、酒精棉签和不棉签对皮肤感染的影响比较

Transaction on Biomedical Engineering Applications and Healthcare Pub Date : 2020-06-15 DOI: 10.36647/tbeah/01.01.a005

Arihant Chhajer

{"title":"Comparison of the Effect of Boiled Cotton Swabs, Alcohol Swabs and Without Swabbing on Skin Infection before an Injection","authors":"Arihant Chhajer","doi":"10.36647/tbeah/01.01.a005","DOIUrl":"https://doi.org/10.36647/tbeah/01.01.a005","url":null,"abstract":"Skin infection is a type of infection that can be caused by bacteria, fungus, viruses or parasites. Nowadays, the world is going through a critical time which has affected the people in many ways and therefore, the people need to take care of their health and health-related problems to save the cost and time without compromising health. For the treatment of skin related infections, the medical professionals uses injections in order to make the patient comfortable and safe. Recommendations about the need to use alcohol before injection of the vaccine are contradictory and based on proof at low rates. Alcohol is used to disinfect the skin prior to injections in order to prevent infections caused by bacteria on the skin being injected within tissue. Alcohol has been shown to be good disinfectant, reducing the number of bacteria on skin by 47-91%. The preparation of skin of the patient before injection is generally done by washing the skin that is visibly soiled or dirty. Swabbing of the clean skin before giving an injection is unnecessary. If swabbing with an antiseptic is selected for use, use a clean, single-use swab and maintain product-specific recommended contact time.Therefore the idea of preparation for the injection site came into effect, but there are different recommendations for preparation of the skin before injection leaving nurses in confusion, and they took up the present analysis. Keyword : Alcohol, Antiseptic, Disinfectant, Skin infection, Swabbing, Treatment, Vaccine.","PeriodicalId":145122,"journal":{"name":"Transaction on Biomedical Engineering Applications and Healthcare","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123090864","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

An Effective Approach for Motion Artifacts Suppression from EEG Signal 一种有效的脑电信号运动伪影抑制方法

Transaction on Biomedical Engineering Applications and Healthcare Pub Date : 2020-06-15 DOI: 10.36647/tbeah/01.01.a001

Rudra Bhanu Satpathy, J. Gavaskar

引用次数: 0

Hybridizing the Dimensionality Reduction Approaches for Cancer Classification Using Genes Expression Analysis 利用基因表达分析杂交降维方法进行癌症分类

Transaction on Biomedical Engineering Applications and Healthcare Pub Date : 2020-06-15 DOI: 10.36647/tbeah/01.01.a004

Ankita Rath, Arihant Chhajer

{"title":"Hybridizing the Dimensionality Reduction Approaches for Cancer Classification Using Genes Expression Analysis","authors":"Ankita Rath, Arihant Chhajer","doi":"10.36647/tbeah/01.01.a004","DOIUrl":"https://doi.org/10.36647/tbeah/01.01.a004","url":null,"abstract":"In the DNA microarray datasets, genes expression has made a big impact on the classification of diseases especially in the case of tumor classification. Tumor classification is basically done to predict the cancer on the basis of genes expression profile. Although genes expression dataset are considered to be high dimensional dataset, so dimensionality reduction is very much needed during the classification. In this work to reduce the dimension of genes expression we have proposed the hybrid approach using ReliefF method and the genetic algorithm. The combination of these methods will be used for selecting the subset of the genes before performing the classification. In this work ReliefF method and genetic algorithm will work as a filter method and wrapper method respectively and there combination will form the hybrid method. The results have shown that the proposed work can be implemented on the genes expression dataset to improve the classification accuracy during the disease prediction. The proposed work has computed the classification accuracy of 94.4%, 96.7%, 96.6% and 90.6% on genes expression of Colon cancer, Leukemia, lung and prostate respectively. Keyword : ReliefF, mutiobjective brain storming, lung cancer, mutation, AUC, accuracy.","PeriodicalId":145122,"journal":{"name":"Transaction on Biomedical Engineering Applications and Healthcare","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121614406","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

Improving the Predicting Rate of Alzheimer's disease through Neuro imaging Data using Deep Learning Approaches 利用深度学习方法通过神经成像数据提高阿尔茨海默病的预测率

Transaction on Biomedical Engineering Applications and Healthcare Pub Date : 2020-06-15 DOI: 10.36647/tbeah/01.01.a003

S. Sahu, S. Swetha

{"title":"Improving the Predicting Rate of Alzheimer's disease through Neuro imaging Data using Deep Learning Approaches","authors":"S. Sahu, S. Swetha","doi":"10.36647/tbeah/01.01.a003","DOIUrl":"https://doi.org/10.36647/tbeah/01.01.a003","url":null,"abstract":"Recently deep learning has shown a improved performance than machine learning in many of the areas like pattern recognition, image classification computer vision, video segmentation and many more. But out of all these areas, disease classification is one of the major area in which deep learning has shown a remarkable performance than the traditional machine learning algorithms especially in the area of image recognition. Machine learning algorithms are not enough capable to handle the image so in this work we will apply the deep learning approach on the Alzheimer's disease dataset for performing the early detection and classification of the disease and this has done through using neuroimaging data. Previous work done in this area was based on traditional machine learning algorithm and they have used stacked auto encoder (SAC) for dimensionality reduction and they have achieved a classification accuracy of 83.7% during the prediction from initial symptom to final development of Alzheimer's disease. The deep learning algorithm ResNet which is implemented in this paper has shown a classification accuracy of 93% and this is also achieved without applying any dimensionality reduction approach and this has been considered as the best predictive rate on the neuroimaging data till now. The applied ResNet is the improved ResNet and the comparison of both the Resnet models are shown in this work. This deep learning application will also be useful for other types of disease classification like cancer, diabetics, etc. Keyword : ResNet, mild cognitive impairments (MCI), ADNI, ReLU, Residual Block, Convolutions.","PeriodicalId":145122,"journal":{"name":"Transaction on Biomedical Engineering Applications and Healthcare","volume":"10 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123283413","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

An Involuntary Single Channel EEG Signals Sleep Stage Detection, Classification and Analysis 非自愿单通道脑电信号睡眠阶段检测、分类与分析

Transaction on Biomedical Engineering Applications and Healthcare Pub Date : 2020-06-15 DOI: 10.36647/tbeah/01.01.a002

Siddth Kumar Chhajer, Rudra Bhanu Satpathy

引用次数: 0