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Challenges and Limitations of Explainable AI in Healthcare
5
Zitationen
2
Autoren
2024
Jahr
Abstract
Explainable AI (XAI) is at the forefront of healthcare innovation. It has the potential to revolutionize clinical decision-making, improve patient care, and transform healthcare delivery. Despite having said that, the integration of XAI into healthcare system is not devoid of challenges and limitations. This chapter explores the multifaceted landscape of shortcomings faced in the process of implementation of XAI in healthcare, providing valuable insights into the complexities and hurdles that needs to be given direction in order to utilize its full potential in interpreting AI in enhancing healthcare results. One of the initial challenges encountered in the implementation of XAI is the inherent complexity of healthcare data. This chapter is an attempt to identify and address challenges and embrace a collaborative commitment to transparency, fairness, and accountability, and also to navigate the complex nature of the Explainable AI in the process of implementation to lead to a new age of interpretable and trustworthy AI-generated healthcare systems.
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