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Hands-On Explainable AI (XAI) with Python

You're reading from   Hands-On Explainable AI (XAI) with Python Interpret, visualize, explain, and integrate reliable AI for fair, secure, and trustworthy AI apps

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Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781800208131
Length 454 pages
Edition 1st Edition
Languages
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Author (1):
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Denis Rothman Denis Rothman
Author Profile Icon Denis Rothman
Denis Rothman
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Table of Contents (16) Chapters Close

Preface 1. Explaining Artificial Intelligence with Python 2. White Box XAI for AI Bias and Ethics FREE CHAPTER 3. Explaining Machine Learning with Facets 4. Microsoft Azure Machine Learning Model Interpretability with SHAP 5. Building an Explainable AI Solution from Scratch 6. AI Fairness with Google's What-If Tool (WIT) 7. A Python Client for Explainable AI Chatbots 8. Local Interpretable Model-Agnostic Explanations (LIME) 9. The Counterfactual Explanations Method 10. Contrastive XAI 11. Anchors XAI 12. Cognitive XAI 13. Answers to the Questions 14. Other Books You May Enjoy
15. Index

The XAI medical diagnosis timeline

We often think we can see a doctor, and we will get a straight explanation of what we are suffering from and what the solution is. Although it might be true in simple cases, it is far from reality in situations in which the symptoms are either absent or difficult to detect. The case study in this chapter describes a case with confusing symptoms and unexpected outcomes.

We can represent such a patient's history, from the diagnosis process to the treatment protocols, in a timeline. A medical diagnosis timeline starts when a doctor first discovers the symptoms of a patient. A simple disease will lead to a rapid diagnosis. When the same symptoms can describe several diseases, the timeline stretches out, and it might take several days or weeks to reach the end of the process and come up with a diagnosis.

Let's introduce a standard AI prototype that will help a general practitioner. The practitioner must deal with...

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