Basic Issues and Challenges on Explainable Artificial Intelligence (XAI) in Healthcare Systems-Reference-Cited by-同舟云学术

Basic Issues and Challenges on Explainable Artificial Intelligence (XAI) in Healthcare Systems

Published:2022-05-20 Issue: Volume: Page:248-271
ISSN:2327-9354
Container-title:Advances in Medical Technologies and Clinical Practice
language:
Short-container-title:

Author:

Dauda Oladipo Idowu¹^ORCID,Awotunde Joseph Bamidele¹^ORCID,Muyideen AbdulRaheem ¹,Salihu Shakirat Aderonke¹

Affiliation:

1. University of Ilorin, Ilorin, Nigeria

Abstract

Artificial intelligence (AI) studies are progressing at a breakneck pace, with prospective programs in healthcare industries being established. In healthcare, there has been an extensive demonstration of the promise of AI through numerous applications like medical support systems and smart healthcare. Explainable artificial intelligence (XAI) development has been extremely beneficial in this direction. XAI models allow smart healthcare equipped with AI models so that the results generated by AI algorithms can be understood and trusted. Therefore, the goal of this chapter is to discuss the utility of XAI in systems used in healthcare. The issues, as well as difficulties related to the usage of XAI models in the healthcare system, were also discussed. The findings demonstrate some examples of XAI's effective medical practice implementation. The real-world application of XAI models in healthcare will significantly improve users' trust in AI algorithms in healthcare systems.

Publisher

IGI Global

Reference90 articles.

1. Abdulhay, E., Arunkumar, N., & Ramirez, G. (n.d.). Explainable Artificial Intelligence for Medical Applications. Hindawi. Retrieved September 20, 2021, from https://www.hindawi.com/journals/jhe/si/658251/

2. Explainable AI for Fighting COVID-19 Pandemic: Opportunities, Challenges, and Future Prospects

3. Explainable AI for healthcare: from black box to interpretable models;A.Adadi;Embedded Systems and Artificial Intelligence,2020

4. Ai, H. (2019). High-level expert group on artificial intelligence. Ethics Guidelines for Trustworthy AI.

5. Prediction and Forecasting of Coronavirus Cases Using Artificial Intelligence Algorithm;S. A.Ajagbe;Machine Learning for Critical Internet of Medical Things,2022

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