Model-specific Explainable Artificial Intelligence techniques: State-of-the-art, Advantages and Limitations

Artificial Intelligence (AI) and Machine learning (ML) applications are being widely used to solve different problems in different sectors. These applications have enabled the human-effort and involvement to be very low. The AI/ML systems<br/>make their own predictions and do not require a great deal of human help. However, over the last few...

Investigation of the evaluation techniques and tools used for model-specific XAI models

The spread of AI techniques has lead to its presence in critical situations, with increasing performance that can compromise on its understanding. Users with no prior AI knowledge rely on these techniques such as doctors or recruiters with a need for transparency and comprehensibility of the mechanisms. The advent of Explainable Artificial...

Food Benefit-Risk Assessment with Bayesian Belief Networks and Multivariable Exposure-Response