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    2. Teknik och industri
    3. Biokemisk teknik

    AI and Data Science in Medical Research

    AvOlfa Boubaker

    Häftad, Engelska, 2026

    Del i serien Medical Robots and Devices: New Developments and Advances

    1 824 kr

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

    Beskrivning

    AI and Data Science in Medical Research focuses on the integration of AI and data science into medical research, highlighting their impact on drug discovery, medical imaging, diagnostics, and genomic medicine. The book addresses the acceleration of therapeutic compound discovery and optimization of drug development pipelines through AI. The volume also discusses advancements in medical imaging, including early disease detection and neuroimaging. Additionally, it covers the application of AI in genomic medicine, offering insights into personalized treatment strategies.

    The volume concludes with an examination of AI's role in public health surveillance, particularly in disease detection and epidemiological research.

    • Emphasizes the integration of AI and data science into medical research, showcasing their influence on drug discovery, medical imaging, diagnostics, and genomic medicine
    • Explores how AI accelerates therapeutic compound discovery and optimizes drug development pipelines, leading to advancements in medical imaging for early disease detection and neuroimaging
    • Covers AI's application in genomic medicine, providing insights into personalized treatment strategies, and a discussion on AI's contribution to public health surveillance, focusing on disease detection and epidemiological research

    Produktinformation

    • Utgivningsdatum:2026-05-08
    • Mått:191 x 235 x 15 mm
    • Vikt:450 g
    • Format:Häftad
    • Språk:Engelska
    • Serie:Medical Robots and Devices: New Developments and Advances
    • Antal sidor:284
    • Förlag:Elsevier Science
    • ISBN:9780443276385

    Utforska kategorier

    • Biokemisk teknik inom Naturvetenskap och teknik
    • Artificiell intelligens inom Data och IT
    • Biomedicinsk teknik inom Medicin

    Mer om författaren

    Olfa Boubaker is a Full Professor at the National Institute of Applied Sciences and Technology (INSAT) at the University of Carthage, Tunisia. Her research spans control theory, nonlinear systems, and robotics, with a focus on healthcare applications and human-centered technologies. She received her PhD in Electrical Engineering from the National Engineering School of Tunis (ENIT) and Habilitation Universitaire degree in Control Engineering from the National Engineering School of Sfax (ENIS), in Tunisia. Professor Boubaker leads interdisciplinary research projects at the interface of medicine and technology and serves as Series Editor of Medical Robots and Devices: New Developments and Advances. She has authored over 150 peer-reviewed papers and several books, and is an Associate Editor for Robotica and the International Journal of Advanced Robotic Systems. She also contributes to various scientific journals and mentors numerous engineering graduates.

    Innehållsförteckning

    • AI and Data Science in Medical Research: An OverviewPart I: Foundations and Core Technologies1. Medical Data Foundations: Key Concepts and Definitions for Clinicians and Researchers2. Artificial Intelligence in Medical Research: Fundamental Methods, Techniques, and Clinical ApplicationsPart II: AI-Driven Diagnosis and Patient Monitoring3. Artificial Intelligence in Neuroimaging: from data acquisition to data analysis4. Synthetic Data for Melanoma Detection: Generative Adversarial Networks and Diffusion Models in Practice5. Voice-Based Deep Learning for Parkinson’s Disease Diagnosis6. Modeling Mpox Transmission Dynamics: Deterministic Approaches Linking Environment and Host InteractionsPart III: Therapeutics, Genomics, and Ethical Perspectives7. AI for Drug Discovery and Development8. Revolutionizing Genomic Medicine with AI and Data Analytics9. AI-Powered Pipelines for Therapeutic Innovation10. Conclusions and Future Directions: Challenges, Opportunities, and Ethical Considerations in AI-Driven Medical Research