Recent Trends in Healthcare Innovation : Proceedings of the Annual International Conference on Recent Trends in Healthcare Innovation (AICRTHI 2024), Mysuru, India, October 24th-25th, 2024

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Recent Trends in Healthcare Innovation : Proceedings of the Annual International Conference on Recent Trends in Healthcare Innovation (AICRTHI 2024), Mysuru, India, October 24th-25th, 2024

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  • 製本 Hardcover:ハードカバー版/ページ数 488 p.
  • 言語 ENG
  • 商品コード 9781032817866
  • DDC分類 362.10285

Full Description

The proceedings of the Annual International Conference on Recent Trends in Healthcare Innovation (AICRTHI 2024) is a compilation of groundbreaking research and advancements in healthcare technology, artificial intelligence, and collaborative healthcare solutions. It serves as a comprehensive reference guide for emerging trends and challenges in modern healthcare innovation.

Drawing on research contributions from experts in academia, industry, and healthcare institutions worldwide, this volume highlights technological breakthroughs in medicine, their implications for patient care, and their potential to reshape the future of global healthcare. It explores collaborative frameworks between technology providers and healthcare practitioners to address pressing healthcare challenges and improve overall public health outcomes. The peer-reviewed papers contained in this book address critical themes in healthcare innovation, with a focus on:

integration of artificial intelligence and machine learning in medical diagnostics
advancements in telemedicine and wearable technologies
innovations in public health and epidemiology
sustainable healthcare practices

This is a valuable resource for healthcare professionals, researchers, academics, and students specializing in healthcare innovation, biomedical engineering, and public health. It is also ideal for policymakers, technologists, and industry leaders interested in leveraging emerging technologies for enhanced healthcare delivery.

Contents

1. Neural network applications

2. AI and ML applications

3. Regression models application

4. Data analysis

5. Reviews

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