Surfacing Best Practices For Ai Software Development And Integration In Healthcare

Surfacing best practices for AI software development and integration in healthcare

Scalable Artificial Intelligence for Healthcare

This edited volume examines the transformative impact of AI technologies on global healthcare systems, with a focus on enhancing efficiency and accessibility. The content provides a comprehensive exploration of the principles and practices required to scale AI applications in healthcare, addressing areas such as diagnosis, treatment, and patient care. Key topics include data scalability, model deployment, and infrastructure design, highlighting the use of microservices, containerization, cloud computing, and big data technologies in building scalable AI systems. Discussions cover advancements in machine learning models, distributed processing, and transfer learning, alongside critical considerations such as continuous integration, data privacy, and ethics. Real-world case studies depict both the successes and challenges of implementing scalable AI across various healthcare environments, offering valuable insights for future advancements. This volume serves as a practical and theoretical guide for healthcare professionals, AI researchers, and technology enthusiasts seeking to develop or expand on AI-driven healthcare solutions to address global health challenges effectively.

Towards Ethical and Socially Responsible Explainable AI

"Dive deep into the evolving landscape of AI with 'Towards Ethical and Socially Responsible Explainable AI'. This transformative book explores the profound impact of AI on society, emphasizing transparency, accountability, and fairness in decision-making processes. It offers invaluable insights into creating AI systems that not only perform effectively but also uphold ethical standards and foster trust. Essential reading for technologists, policymakers, and all stakeholders invested in shaping a responsible AI future."