Description

Book Synopsis
There are several popular books published in Healthcare Computational Informatics like Computational Bioengineering and Bioinformatics (2020), Springer; Health Informatics (2017), Springer; Health Informatics Vision: From Data via Information to Knowledge (2019), IOS Press; Data Analytics in Biomedical Engineering and Healthcare (2020), Elsevier. However, in all these mentioned books, the challenges in Biomedical Imaging are solved in one dimension by use of any specific technology like Image Processing, Machine Learning or Computer Aided Systems. In this book, the book it has been attempted to bring all technologies related to computational analytics together and apply them on Biomedical Imaging.

Table of Contents

Section 1: Medical Image Analysis using Artificial Intelligence

Use of Deep Learning in Biomedical Imaging

Detection of Breast Cancer Masses in Mammogram Images with Watershed Segmentation and Machine Learning Approach

Cloud-based Glaucoma Diagnosis in Medical Imaging using Machine Learning

Leucocytic Cell Nucleus Identification using Boundary Cell Detection algorithm with Dilation and Erosion based Morphometry

Effective Prediction of Autism Using Ensemble Method

Section 2: Artificial Intelligence (AI) Classification Models for COVID-19 Pandemic

Automatic Classification of COVID-19 infected patients using Convolution Neural Network Models

AI-Based Deep Random Forest Ensemble Model for Prediction of COVID-19 and Pneumonia from Chest X-Ray Images

Section 3: Use of AI-Enabled IoT in Healthcare

Internet of Things and Artificial Intelligence in Biomedical Systems

Role of IoT in Healthcare Sector for Monitoring Diabetic Patients

Section 4: Applications of Artificial Intelligence in Healthcare

Low-Rank Representation based approach for subspace segmentation and clustering of biomedical image patterns

Performance Comparison of Imputation Methods for Heart Disease Prediction

Ayurnano: A solution towards herbal therapeutics using Artificial Intelligence approach

Artificial Intelligence in Biomedical Education

The Emergence of Natural Language Processing (NLP) Techniques in Healthcare AI

Prospects and Difficulties of Artificial Intelligence (AI) Implementations in Naturopathy

Artificial Intelligence for Innovative Healthcare

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A Hardback by Shabir Ahmad Parah, Mamoon Rashid, Vijayakumar Varadarajan

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    View other formats and editions of Artificial Intelligence for Innovative Healthcare by Shabir Ahmad Parah

    Publisher: Springer Nature Switzerland AG
    Publication Date: 24/05/2022
    ISBN13: 9783030965686, 978-3030965686
    ISBN10: 3030965686

    Description

    Book Synopsis
    There are several popular books published in Healthcare Computational Informatics like Computational Bioengineering and Bioinformatics (2020), Springer; Health Informatics (2017), Springer; Health Informatics Vision: From Data via Information to Knowledge (2019), IOS Press; Data Analytics in Biomedical Engineering and Healthcare (2020), Elsevier. However, in all these mentioned books, the challenges in Biomedical Imaging are solved in one dimension by use of any specific technology like Image Processing, Machine Learning or Computer Aided Systems. In this book, the book it has been attempted to bring all technologies related to computational analytics together and apply them on Biomedical Imaging.

    Table of Contents

    Section 1: Medical Image Analysis using Artificial Intelligence

    Use of Deep Learning in Biomedical Imaging

    Detection of Breast Cancer Masses in Mammogram Images with Watershed Segmentation and Machine Learning Approach

    Cloud-based Glaucoma Diagnosis in Medical Imaging using Machine Learning

    Leucocytic Cell Nucleus Identification using Boundary Cell Detection algorithm with Dilation and Erosion based Morphometry

    Effective Prediction of Autism Using Ensemble Method

    Section 2: Artificial Intelligence (AI) Classification Models for COVID-19 Pandemic

    Automatic Classification of COVID-19 infected patients using Convolution Neural Network Models

    AI-Based Deep Random Forest Ensemble Model for Prediction of COVID-19 and Pneumonia from Chest X-Ray Images

    Section 3: Use of AI-Enabled IoT in Healthcare

    Internet of Things and Artificial Intelligence in Biomedical Systems

    Role of IoT in Healthcare Sector for Monitoring Diabetic Patients

    Section 4: Applications of Artificial Intelligence in Healthcare

    Low-Rank Representation based approach for subspace segmentation and clustering of biomedical image patterns

    Performance Comparison of Imputation Methods for Heart Disease Prediction

    Ayurnano: A solution towards herbal therapeutics using Artificial Intelligence approach

    Artificial Intelligence in Biomedical Education

    The Emergence of Natural Language Processing (NLP) Techniques in Healthcare AI

    Prospects and Difficulties of Artificial Intelligence (AI) Implementations in Naturopathy

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