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Health Information Science and Systems - Call for Papers: Exploring the Potential of Explainable AI in Improving Healthcare

Title:  Exploring the Potential of Explainable AI in Improving Healthcare

Introduction:

Artificial intelligence (AI) is transforming the healthcare industry by enabling more accurate diagnoses, personalized treatment plans, and improved patient outcomes. However, the lack of transparency and interpretability of AI models has hindered its widespread adoption, particularly in healthcare where the need for trust and transparency is critical. Explainable AI (XAI) is a rapidly growing field that seeks to address this issue by making AI models more transparent and interpretable, enabling users to understand how the models make their predictions and recommendations. This special issue aims to explore the potential of XAI in improving healthcare decision-making and patient outcomes. The papers in this issue will provide insights into the applications, challenges, and opportunities for implementing XAI in healthcare and will contribute to the development of guidelines and best practices for its use.

We invite original research articles, review papers, and case studies that focus on the potential of XAI in healthcare decision-making and patient outcomes. All submissions must be written in English and follow the formatting guidelines of the journal. Submitted manuscripts will undergo a rigorous peer-review process, and only high-quality papers that meet the standards of the journal will be accepted for publication.

Keywords:

  • Applications of XAI in healthcare decision-making, including diagnosis, treatment planning, and clinical decision support 
  • Evaluation of XAI models in healthcare settings
  • Ethical, legal, and social implications of XAI in healthcare user-centered design of XAI for healthcare
  • Interpretable machine learning techniques for healthcare challenges and opportunities for implementing XAI in healthcare 
  • The role of explainable AI in improving diagnostic accuracy in healthcareExplainable AI for personalized treatment planning and optimization in healthcare
  • Ethical and legal considerations in the use of explainable AI in healthcare
  • Explainable AI for clinical decision support and decision-making in healthcare
  • Explainable AI for monitoring and improving healthcare quality and patient outcomes
  • AI with blockchain for privacy ensuring decision-making

Guest Editors:

Tentative Time Schedule:

Submission deadline: October 30, 2023

First review completed: November 29, 2023

Revised manuscript due: March 30, 2024

Second review completed: April 29, 2024

Possible Publication: May 30, 2024

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