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Modelling a Fused Deep network Model for Pneumonia Prediction

Computer Systems Science & Engineering 2023年第9期46卷 2725-2739页

作者： M.A.Ramitha n.mohanasundaram R.Santhosh Department of Computer Science and Engineering Karpagam Academy of Higher EducationCoimbatoreIndia

Deep Learning(DL)is known for its golden standard computing paradigm in the learning ***,it turns out to be an extensively utilized computing approach in the ML ***,attaining superior outcomes over cognitive tasks based on human *** primary benefit of DL is its competency in learning massive *** DL-based technologies have grown faster and are widely adopted to handle the conventional approaches ***,various DL approaches outperform the conventional ML approaches in real-time ***,various research works are reviewed to understand the significance of the individual DL models and some computational complexity is *** may be due to the broader expertise and knowledge required for handling these models during the prediction *** research proposes a holistic approach for pneumonia prediction and offers a more appropriate DL model for classification *** work incorporates a novel fused Squeeze and Excitation(SE)block with the Resnet model for pneumonia prediction and better *** expected model reduces the human effort during the prediction process and makes it easier to diagnose it intelligently as the feature learning is *** experimentation is carried out in Keras,and the model’s superiority is compared with various advanced *** proposed model gives 90%prediction accuracy,93%precision,90%recall and 89%*** proposed model shows a better trade-off compared to other *** evaluation is done with the existing standard Resnet model,Googlenet+Resnet+Densenet,and different variants of Resnet models.

关键词： Disease prediction pneumonia deep learning SE Resnet fused network model

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Earlier Detection of Alzheimer’s Disease Using 3D-Convolutional neural networks

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Computer Systems Science & Engineering 2023年第8期46卷 2601-2618页

作者： V.P.nithya n.mohanasundaram R.Santhosh Department of Computer Science and Engineering Karpagam Academy of Higher EducationCoimbatoreIndia

The prediction of mild cognitive impairment or Alzheimer’s disease(AD)has gained the attention of huge researchers as the disease occurrence is increasing,and there is a need for earlier ***,due to the highdimensionality nature of neural data and the least available samples,modelling an efficient computer diagnostic system is highly *** approaches,specifically deep learning approaches,are essential in disease *** Learning(DL)approaches are successfully demonstrated for their higher-level performance in various fields like medical imaging.A novel 3D-Convolutional neural network(3D-Cnn)architecture is proposed to predict AD with Magnetic resonance imaging(MRI)*** proposed model predicts the AD occurrence while the existing approaches lack prediction accuracy and perform binary *** proposed prediction model is validated using the Alzheimer’s disease neuro-Imaging Initiative(ADnI)*** outcomes demonstrate that the anticipated model attains superior prediction accuracy and works better than the brain-image dataset’s general *** predicted model reduces the human effort during the prediction process and makes it easier to diagnose it intelligently as the feature learning is ***’experimentation is carried out,and the model’s superiority is compared with various advanced approaches for multi-level *** proposed model gives better prediction accuracy,precision,recall,and F-measure than other systems like Long Short Term Memory-Recurrent neural networks(LSTM-Rnn),Stacked Autoencoder with Deep neural networks(SAE-Dnn),Deep Convolutional neural networks(D-Cnn),Two Dimensional Convolutional neural networks(2D-Cnn),Inception-V4,Resnet,and Two Dimensional Convolutional neural networks(3D-Cnn).

关键词： Alzheimer’s disease 3D Cnn ADnI prediction accuracy highdimensionality data

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Tuberculosis in kidney transplant candidates and recipients

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World Journal of Transplantation 2024年第3期14卷 59-69页

作者： Pallavi Prasad Sourabh Sharma Subashri mohanasundaram Anupam Agarwal Himanshu Verma Department of nephrology Vardhman Mahavir Medical College and Safdarjung HospitalNew Delhi 110029DelhiIndia Department of nephrology Prashanth HospitalChennai 600042Tamil NāduIndia

Tuberculosis(TB)is the leading cause of infectious mortality and morbidity in the world,second only to coronavirus disease *** with chronic kidney disease and kidney transplant recipients are at a higher risk of developing TB than the general *** TB is difficult to diagnose in this population due to close *** transplant candidates should be screened for latent TB infection and given TB *** who develop active TB pre-or post-trans-plantation should receive multidrug combination therapy of antitubercular therapy for the recommended duration with optimal dose modification as per glomerular filtration rate.

关键词： Tuberculosis Latent Antitubercular therapy Kidney transplantation Donor Interferon-gamma release assays Tuberculin Rifampicin Isoniazid

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