Directive Explanations for Monitoring the Risk of Diabetes Onset: Introducing Directive Data-Centric Explanations and Combinations to Support What-If Explorations

Author:

Bhattacharya Aditya1ORCID,Ooge Jeroen1ORCID,Stiglic Gregor2ORCID,Verbert Katrien1ORCID

Affiliation:

1. Computer Science, KU Leuven, Belgium

2. University of Maribor, Slovenia

Funder

FWO

KU Leuven Internal Funds

Publisher

ACM

Reference79 articles.

1. Trends and Trajectories for Explainable, Accountable and Intelligible Systems

2. Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)

3. Data-Centric Explanations: Explaining Training Data of Machine Learning Systems to Promote Transparency

4. Current Challenges and Future Opportunities for XAI in Machine Learning-Based Clinical Decision Support Systems;Antoniadi Anna Markella;A Systematic Review. Applied Sciences,2021

5. Aditya Bhattacharya . 2022. Applied Machine Learning Explainability Techniques . In Applied Machine Learning Explainability Techniques . Packt Publishing , Birmingham, UK . https://www.packtpub.com/product/applied-machine-learning-explainability-techniques/978 1803 246154 Aditya Bhattacharya. 2022. Applied Machine Learning Explainability Techniques. In Applied Machine Learning Explainability Techniques. Packt Publishing, Birmingham, UK. https://www.packtpub.com/product/applied-machine-learning-explainability-techniques/9781803246154

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