Description

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Table of Contents
1. A deep learning approach for the prediction of heart attacks based on data analysis 2. A comparative study on fully convolutional networks—FCN-8, FCN-16, and FCN-32: A case of brain tumor 3. Deep learning applications for disease diagnosis 4. An artificial intelligent cognitive approach for classification and recognition of white blood cells employing deep learning for medical applications 5. Deep learning on medical image analysis on COVID-19 x-ray dataset using an X-Net architecture 6. Early prediction of heart disease using a deep learning approach 7. Machine learning and deep learning algorithms in disease prediction: Future trends for the healthcare system 8. Automatic detection of white matter hyperintensities via mask region-based convolutional neural networks using magnetic resonance images 9. Diagnosing glaucoma with optic disk segmenting and deep learning from color retinal fundus images 10. An artificial intelligence framework to ensure a trade-off between sanitary and economic perspectives during the COVID-19 pandemic 11. Prediction of COVID-19 using machine learning techniques

Deep Learning for Medical Applications with

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A Paperback / softback by Deepak Gupta, Utku Kose, Ashish Khanna

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    View other formats and editions of Deep Learning for Medical Applications with by Deepak Gupta

    Publisher: Elsevier Science Publishing Co Inc
    Publication Date: 17/02/2022
    ISBN13: 9780128241455, 978-0128241455
    ISBN10: 0128241454
    Also in:
    Biomedical engineering / Medical engineering Technology, Engineering & Agriculture Biotechnology

    Description

    Book Synopsis


    Table of Contents
    1. A deep learning approach for the prediction of heart attacks based on data analysis 2. A comparative study on fully convolutional networks—FCN-8, FCN-16, and FCN-32: A case of brain tumor 3. Deep learning applications for disease diagnosis 4. An artificial intelligent cognitive approach for classification and recognition of white blood cells employing deep learning for medical applications 5. Deep learning on medical image analysis on COVID-19 x-ray dataset using an X-Net architecture 6. Early prediction of heart disease using a deep learning approach 7. Machine learning and deep learning algorithms in disease prediction: Future trends for the healthcare system 8. Automatic detection of white matter hyperintensities via mask region-based convolutional neural networks using magnetic resonance images 9. Diagnosing glaucoma with optic disk segmenting and deep learning from color retinal fundus images 10. An artificial intelligence framework to ensure a trade-off between sanitary and economic perspectives during the COVID-19 pandemic 11. Prediction of COVID-19 using machine learning techniques

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