Responsible and Explainable Artificial Intelligence in Healthcare : Ethics and Transparency at the Intersection / Singh, Akansha (EDT)/ Singh, Krishna Kant (EDT)/ Izonin, Ivan (EDT)

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Responsible and Explainable Artificial Intelligence in Healthcare : Ethics and Transparency at the Intersection

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Responsible and Explainable Artificial Intelligence in Healthcare : Ethics and Transparency at the Intersection

Singh, Akansha (EDT)/ Singh, Krishna Kant (EDT)/ Izonin, Ivan (EDT)

ウェブストア価格 ¥42,803（本体¥38,912）
Academic Press Inc（2024/11発売）
外貨定価 US$ 200.00
読書週間ポイント2倍キャンペーン対象商品（～11/9）
ポイント 778pt

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製本 Paperback:紙装版/ペーパーバック版／ページ数 314 p.
言語 ENG
商品コード 9780443247880
DDC分類 610.28563

Full Description

Responsible and Explainable Artificial Intelligence in Healthcare: Ethics and Transparency at the Intersection provides clear guidance on building trustworthy Artificial Intelligence systems for healthcare. The book focuses on using Artificial Intelligence to improve diagnosis, prevent diseases, and personalize patient care. It addresses potential drawbacks, like reduced human interaction and ethical concerns, offering solutions for ethical and transparent Artificial Intelligence use in medicine. Across eight chapters, the book explores Artificial Intelligence's current status, its importance, and associated risks in healthcare. It explains designing reliable Artificial Intelligence for healthcare, tackling biases, and safeguarding patient privacy in the age of big data. The legal and regulatory landscape is also covered. One chapter is dedicated to showcasing real-world examples of responsible Artificial Intelligence in healthcare, highlighting best practices. The book concludes by summarizing key takeaways and discussing future challenges. "Responsible and Explainable Artificial Intelligence in Healthcare: Ethics and Transparency at the Intersection" is a valuable resource for healthcare professionals, policymakers, computer scientists, and ethicists concerned about Artificial Intelligence's ethical and societal impact on medicine.

1. Revolutionizing Healthcare: The Transformative Role of Artificial Intelligence
2. Ethical Considerations in AI Powered Diagnosis and Treatment
3. Explainable AI Methods to Increase Trustworthiness in Healthcare
4. Designing Transparent and Accountable AI Systems for Healthcare
5. Ensuring Fairness and Mitigating Bias in Healthcare AI Systems
6. AI Enhanced Healthcare: Opportunities, Challenges, Ethical Considerations, and Future Risk
7. Healthcare Revolution: Advances in AI-Driven Medical Imaging and Diagnosis
8. A Deep Learning Approach for Medical Image Classification Using XAI and Convolutional Neural Networks
9. Hybrid Ensemble Learning Model to Improve the Performance and Interpretability of Medical Diagnosis: Small Data Tasks
10. Legal and Regulatory Issues Related to AI in Healthcare
11. Responsible and Explainable Artificial Intelligence in Healthcare: Conclusion and Future Directions