Analyzing Explainable AI in Healthcare and the Pharmaceutical Industry

Analyzing Explainable AI in Healthcare and the Pharmaceutical Industry

Veena Grover, Balamurugan Balusamy, Nallakaruppan M.K., Vijay Anand, Mariofanna Milanova
Release Date: June, 2024|Copyright: © 2024 |Pages: 294
DOI: 10.4018/979-8-3693-5468-1
ISBN13: 9798369354681|ISBN13 Softcover: 9798369354698|EISBN13: 9798369354704
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Description & Coverage
Description:

Healthcare and pharmaceuticals are rapidly advancing with technological innovations, and the lack of understanding of AI algorithms poses a significant challenge in these fields. The need for more transparency in AI decision-making processes raises concerns about accountability, ethical implications, and regulatory compliance. As stakeholders in these critical sectors seek clarity and understanding, Analyzing Explainable AI in Healthcare and the Pharmaceutical Industry provides a reliable resource to discover new solutions.

This book serves as a comprehensive guide, unraveling the complexities of explainable artificial intelligence (XAI) and its pivotal role in transforming healthcare and pharmaceutical practices. Demystifying AI algorithms and revealing their decision-making mechanisms equips readers with the foundational knowledge needed to confidently navigate AI integration in these domains. From healthcare professionals to policymakers, its insights cater to a diverse audience, fostering cross-disciplinary collaboration and facilitating informed decision-making.

Through real-world case studies, ethical explorations, and regulatory insights, this book addresses the challenges posed by unclear AI processes and provides actionable solutions. Promoting transparency, fairness, and accountability empowers stakeholders to harness the full potential of XAI while mitigating risks and ensuring compliance. This book emerges as a vital resource, guiding the journey towards responsible and impactful AI adoption in healthcare and pharmaceutical settings.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Accountability in Healthcare Technologies
  • Applications of Artificial Intelligence in Healthcare Settings
  • Bias Mitigation
  • Clinical Support
  • Drug Discovery
  • Ethical Considerations
  • Future Predictions for AI in Healthcare
  • Human-Centric Approaches
  • Improved Decision-Making
  • Interpretable Models of AI
  • Legal Compliance
  • Medical Diagnostics
  • Patient Trust
  • Understanding Algorithms
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Editor/Author Biographies
Veena Grover is currently working as Professor in Department of Management at Noida Institute of Engineering & Technology, Greater Noida, UP, India. Prior to this, she had been working as Professor in School of Business, Galgotias University, she has more than 21 years of teaching experience in educational institutions of repute like Lingaya’s University, New Delhi Institute of Management, University of Delhi, DAV Institute of Management etc. She is Gold Medallist & University topper in Economics. She has got many appreciation letters for her teaching & administrative skills over the years. Her research interests include Micro Finance, Sustainability, Macro Economic Variables and Innovation Strategy. She has published various articles in various journals and presented papers in various international conferences. She serves as an Editor of the refereed journal, International Journal of Advanced Trends in Technology, Management & Applied Science. Dr. Veena Grover earned her PhD from Department of Business Administration, Deenbandhu Chhotu Ram University of Science & Technology, Murthal (Sonepat).
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