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

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. Gives insights into the responsible and explainable use of Artificial Intelligence in healthcare and explore the challenges and opportunities for promoting ethical and transparent practices in this fieldOffers the solution to strike a balance between patient privacy and data exchangeProvides concrete advice on how to create trustworthy, accountable, and transparent Artificial Intelligence systemsExplains the moral and social effects of Artificial intelligence in healthcare and suggests ways to encourage its ethical application INDICE: 1. Revolutionizing Healthcare: The Transformative Role of Artificial Intelligence2. Ethical Considerations in AI Powered Diagnosis and Treatment3. Explainable AI Methods to Increase Trustworthiness in Healthcare4. Designing Transparent and Accountable AI Systems for Healthcare5. Ensuring Fairness and Mitigating Bias in Healthcare AI Systems6. AI Enhanced Healthcare: Opportunities, Challenges, Ethical Considerations, and Future Risk7. Healthcare Revolution: Advances in AI-Driven Medical Imaging and Diagnosis8. A Deep Learning Approach for Medical Image Classification Using Xai and Convolutional Neural Networks9. Hybrid Ensemble Learning Model to Improve the Performance and Interpretability of Medical Diagnosis: Small Data Tasks10. Legal and Regulatory Issues Related to AI in Healthcare11. Responsible and Explainable Artificial Intelligence in Healthcare: Conclusion and Future Directions

• ISBN: 978-0-443-24788-0
• Editorial: Academic Press
• Encuadernacion: Rústica
• Páginas: 320
• Fecha Publicación: 01/12/2024
• Nº Volúmenes: 1
• Idioma: Inglés