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Brain tumour segmentation using deep learning method - inception U-net 使用深度学习的脑肿瘤分割方法-初始U-net
Q3 Medicine Pub Date : 2023-01-01 DOI: 10.1504/ijmei.2023.10058262
B. Kannan, G. Gurumoorthy, B. Ramesh, S. Mohan
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引用次数: 0
A new Parkinson detection system based on evolutionary fast learning networks and voice measurements 基于进化快速学习网络和语音测量的帕金森检测系统
Q3 Medicine Pub Date : 2023-01-01 DOI: 10.1504/ijmei.2023.130731
Ayoub Bouslah, Nora Taleb
Parkinson's disease (PD) is becoming the second most neurological syndrome of the central nervous system after Alzheimer's disease. It causes diverse symptoms which include bradykinesia (slowness of movement), voice impairments, rigidity, tremor, and poor balance. PD recognition system based on voice has founded a non-invasive alternative, but involves rather complex measurements or variables. Therefore an attention is required toward new approaches for better forecasting accuracy. In this paper, an optimal fast learning network (FLN) based on genetic algorithm (GA) was established as PD diagnosis system. FLN is a double-parallel feed-forward neural network structure, and based on GA for feature reduction and hyperparameter optimisation of the FLN, it was used as a predictive model. Finally, the conducted experiments on the Parkinson data of voice recordings over ten fold cross-validation show that proposed system is less complex and also achieved better average classification results with an accuracy of 97.47%. At the same time, it is effective in automatic identification of important vocal features. Moreover, the highest average degree of improved accuracy was (2.1%) compared with other familiar wrappers including support vector machine and K-nearest neighbours in the similar conditions.
帕金森病(PD)正在成为仅次于阿尔茨海默病的中枢神经系统第二大神经系统综合征。它会导致多种症状,包括运动迟缓(运动缓慢)、声音障碍、僵硬、震颤和平衡能力差。基于语音的PD识别系统已经建立了一种非侵入性的替代方法,但涉及到相当复杂的测量或变量。因此,需要注意采用新的方法来提高预测的准确性。本文建立了一种基于遗传算法(GA)的最优快速学习网络(FLN)作为PD诊断系统。FLN是一种双并行前馈神经网络结构,基于遗传算法对FLN进行特征约简和超参数优化,并将其作为预测模型。最后,对录音的帕金森数据进行了十倍以上的交叉验证实验,结果表明,本文提出的系统复杂性较低,平均分类结果也较好,准确率达到97.47%。同时,对重要的声音特征进行自动识别是有效的。此外,在类似条件下,与其他熟悉的包装器(包括支持向量机和k近邻)相比,最高的平均精度提高程度为(2.1%)。
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引用次数: 1
Automatic speech classification in school children with cleft (and lip) palate 腭裂(唇)学童的自动语音分类
Q3 Medicine Pub Date : 2023-01-01 DOI: 10.1504/ijmei.2023.133088
Khaled Baazi, Mhania Guerti
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引用次数: 0
Automatic speech classification in school children with cleft (and lip) palate 腭裂(唇)学童的自动语音分类
Q3 Medicine Pub Date : 2023-01-01 DOI: 10.1504/ijmei.2021.10041983
Khaled Baazi, M. Guerti
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引用次数: 0
Multi perceptron network based model to classify the multi stages of Alzheimer’s disease using clinical data 基于多感知器网络的阿尔茨海默病多阶段临床数据分类模型
Q3 Medicine Pub Date : 2023-01-01 DOI: 10.1504/ijmei.2023.10056957
M. Kusuma, C. R. Nagarathna
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引用次数: 0
Parkinsons detection based on combined ResNet architecture and LSTM 基于联合ResNet和LSTM的帕金森检测
Q3 Medicine Pub Date : 2023-01-01 DOI: 10.1504/ijmei.2023.10057280
B. Bapu, K. Kiruthika, M. Gokuldhev, A. Kumar
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引用次数: 0
Radial basis function network equipped with an ensemble-based Lasso ridge model in diagnosis of breast cancer 基于集成Lasso脊模型的径向基函数网络在乳腺癌诊断中的应用
Q3 Medicine Pub Date : 2023-01-01 DOI: 10.1504/ijmei.2023.10056107
Pooja J. Shah, T. Shah
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引用次数: 0
A new hybrid approach for automated leakage detection in fundus fluorescein angiography images 眼底荧光素血管造影图像自动渗漏检测的新混合方法
Q3 Medicine Pub Date : 2023-01-01 DOI: 10.1504/ijmei.2023.10056108
S. K. Banchhor, B. Singh, Suraj Chandrakar, Ankur Khare, R. Khatri, Deepak Chandravanshi
{"title":"A new hybrid approach for automated leakage detection in fundus fluorescein angiography images","authors":"S. K. Banchhor, B. Singh, Suraj Chandrakar, Ankur Khare, R. Khatri, Deepak Chandravanshi","doi":"10.1504/ijmei.2023.10056108","DOIUrl":"https://doi.org/10.1504/ijmei.2023.10056108","url":null,"abstract":"","PeriodicalId":39126,"journal":{"name":"International Journal of Medical Engineering and Informatics","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66719870","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
Revolutionising organ donation and transplantation for a better future: a blockchain based approach 为更美好的未来革新器官捐赠和移植:基于区块链的方法
Q3 Medicine Pub Date : 2023-01-01 DOI: 10.1504/ijmei.2023.10058768
R. Patil, Yogesh H. Patil
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引用次数: 0
Multi-task deep neural network models for learning COVID-19 disease representations from multimodal data 基于多模态数据学习COVID-19疾病表征的多任务深度神经网络模型
Q3 Medicine Pub Date : 2023-01-01 DOI: 10.1504/ijmei.2023.134537
Veena Mayya, K. Karthik, Krishnananda Prabhu Karadka, S. Sowmya Kamath
{"title":"Multi-task deep neural network models for learning COVID-19 disease representations from multimodal data","authors":"Veena Mayya, K. Karthik, Krishnananda Prabhu Karadka, S. Sowmya Kamath","doi":"10.1504/ijmei.2023.134537","DOIUrl":"https://doi.org/10.1504/ijmei.2023.134537","url":null,"abstract":"","PeriodicalId":39126,"journal":{"name":"International Journal of Medical Engineering and Informatics","volume":"303 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134883383","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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International Journal of Medical Engineering and Informatics
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