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    1. Data och IT
    2. Systemvetenskap och AI

    Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications

    AvOm Prakash Jena,Bharat Bhushan

    Häftad, Engelska, 2024

    Del i serien Biomedical and Robotics Healthcare

    799 kr

    Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

    Beskrivning

    Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications introduces and explores a variety of schemes designed to empower, enhance, and represent multi-institutional and multi-disciplinary machine learning (ML) and deep learning (DL) research in healthcare paradigms. Serving as a unique compendium of existing and emerging ML/DL paradigms for the healthcare sector, this book demonstrates the depth, breadth, complexity, and diversity of this multi-disciplinary area. It provides a comprehensive overview of ML/DL algorithms and explores the related use cases in enterprises such as computer-aided medical diagnostics, drug discovery and development, medical imaging, automation, robotic surgery, electronic smart records creation, outbreak prediction, medical image analysis, and radiation treatments. This book aims to endow different communities with the innovative advances in theory, analytical results, case studies, numerical simulation, modeling, and computational structuring in the field of ML/DL models for healthcare applications. It will reveal different dimensions of ML/DL applications and will illustrate their use in the solution of assorted real-world biomedical and healthcare problems. Features: Covers the fundamentals of ML and DL in the context of healthcare applications Discusses various data collection approaches from various sources and how to use them in ML/DL models Integrates several aspects of AI-based computational intelligence such as ML and DL from diversified perspectives which describe recent research trends and advanced topics in the field Explores the current and future impacts of pandemics and risk mitigation in healthcare with advanced analytics Emphasizes feature selection as an important step in any accurate model simulation where ML/DL methods are used to help train the system and extract the positive solution implicitly This book is a valuable source of information for researchers, scientists, healthcare professionals, programmers, and graduate-level students interested in understanding the applications of ML/DL in healthcare scenarios.Dr. Om Prakash Jena is an Assistant Professor in the Department of Computer Science, Ravenshaw University, Cuttack, Odisha, India.Dr. Bharat Bhushan is an Assistant Professor of Department of Computer Science and Engineering (CSE) at the School of Engineering and Technology, Sharda University, Greater Noida, India.Dr. Utku Kose is an Associate Professor in Suleyman Demirel University, Turkey.

    Produktinformation

    • Utgivningsdatum:2024-10-04
    • Mått:156 x 234 x 16 mm
    • Vikt:426 g
    • Format:Häftad
    • Språk:Engelska
    • Serie:Biomedical and Robotics Healthcare
    • Antal sidor:280
    • Förlag:Taylor & Francis Ltd
    • ISBN:9781032127644

    Utforska kategorier

    • Systemvetenskap och AI inom Data och IT
    • Biokemisk teknik inom Naturvetenskap och teknik
    • Biomedicinsk teknik inom Medicin

    Mer om författaren

    Om Prakash Jena is an Assistant Professor in the Department of Computer Science, Ravenshaw University, Cuttack, Odisha, India.Dr. Bharat Bhushan is an Assistant Professor of Department of Computer Science and Engineering (CSE) at School of Engineering and Technology, Sharda University, Greater Noida, India. Dr. Utku Kose is an Associate Professor in Suleyman Demirel University, Turkey.

    Innehållsförteckning

    • Chapter 1 Common Data Interface for Sustainable Healthcare SystemC. B. Abhilash, K. T. Deepak, Rajendra Hegadi, and Kavi MaheshChapter 2 Brain–Computer Interface: Review, Applications and ChallengesPrashant Sengar and Shawli BardhanChapter 3 Three-Dimensional Reconstruction and Digital Printing of Medical Objects in Purview of Clinical ApplicationsSushitha Susan Joseph and Aju DChapter 4 Medical Text and Image Processing: Applications, Methods, Issues, and ChallengesBehzad Soleimani Neysiani and Hassan HomayounChapter 5 Usage of ML Techniques for ASD Detection: A Comparative Analysis of Various ClassifiersAshima Sindhu Mohanty, Priyadarsan Parida, and Krishna Chandra PatraChapter 6 A Framework for Selection of Machine Learning Algorithms Based on Performance Metrices and Akaike Information Criteria in Healthcare, Telecommunication, and Marketing SectorA. K. Hamisu and K. JasleenChapter 7 Hybrid Marine Predator Algorithm with Simulated Annealing for Feature SelectionUtkarsh Mahadeo Khaire, R. Dhanalakshmi, and K. BalakrishnanChapter 8 Survey of Deep Learning Methods in Image Recognition and Analysis of Intrauterine ResiduesBhawna Swarnkar, Nilay Khare, and Manasi GyanchandaniChapter 9 A Comprehensive Survey on Breast Cancer Thermography Classification Using Deep Neural NetworkAmira Hassan Abed, Essam M Shaaban, Om Prakash Jena, and Ahmed A. ElngarChapter 10 Deep Learning Frameworks for Prediction, Classification and Diagnosis of Alzheimer’s DiseaseNitin Singh Rajput, Mithun Singh Rajput, and Purnima Dey SarkarChapter 11 Machine Learning Algorithms and COVID-19: A Step for Predicting Future Pandemics with a Systematic OverviewMadhumita Pal, Ruchi Tiwari, Kuldeep Dhama, Smita Parija, Om Prakash Jena, and Ranjan K. MohapatraChapter 12 TRNetCoV: Transferred Learning-based ResNet Model for COVID-19 Detection Using Chest X-ray ImagesG. V. Eswara Rao and B. RajithaChapter 13 The Influence of COVID-19 on Air Pollution and Human HealthL. Bouhachlaf, J. Mabrouki, and S. El HajjajiChapter 14 Smart COVID-19 GeoStrategies using Spatial Network Voronoï DiagramsA. Mabrouk and A. BoulmakoulChapter 15 Healthcare Providers Recommender System Based on Collaborative Filtering TechniquesAbdelaaziz Hessane, Ahmed El Youssefi, Yousef Farhaoui, Badraddine Aghoutane, Noureddine Ait Ali, and Ayasha Malik
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