Scalable Artificial Intelligence for Healthcare

Advancing AI Solutions for Global Health Challenges

AvHouneida Sakly,Ramzi Guetari

Häftad, Engelska, 2025

Del i serien Analytics and AI for Healthcare

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Beskrivning

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.

Produktinformation

Utgivningsdatum:2025-05-05
Mått:156 x 234 x 12 mm
Vikt:280 g
Format:Häftad
Språk:Engelska
Serie:Analytics and AI for Healthcare
Antal sidor:154
Förlag:Taylor & Francis Ltd
ISBN:9781032769592

Utforska kategorier

Systemvetenskap och AI inom Data och IT
Artificiell intelligens inom Data och IT
Hälso- och sjukvård inom Medicin

Mer om författaren

Houneida Sakly is an Assistant Professor at CRMN in Tunisia’s Sousse Techno Park. Holding a Ph.D. from ENSI in partnership with French universities (Gustave Eiffel University –ESIEE-Paris and Polytech-Orléans), she specializes in data science applied to healthcare. She collaborates with Stanford and is certified by MIT-Harvard in healthcare innovation.Ramzi Guetari is an Associate Professor of Computer Science at the Polytechnic School of Tunisia. He achieved his Ph.D. at the University of Savoie, France, worked at the INRIA, contributed to W3C standards, and now studies AI and machine learning, collaborating with international organizations and companies.Naoufel Kraiem is a Full Professor of Computer Science with 32 years in academia. He earned his Ph.D. at the University of Paris 6 and Habilitation from Sorbonne University. His research spans IT, data science, and software engineering, supported by the CNRS, INRIA, and EU programs, with over 147 publications.

Innehållsförteckning

Table of Contents1. AI in Healthcare: Addressing Challenges and Enabling TransformationHouneida Sakly, Ramzi Guetari, Naoufel Kraiem and Mourad Said2. Fundamental Principles of AI Scalability in HealthcareAbdallah Ahmed Wajdi, Houneida Sakly, Ramzi Guetari and Naoufel Kraiem3. Architectures for Scalable AI in HealthcareHouneida Sakly, Ramzi Guetari, Naoufel Kraiem and Mourad Abed4. Big Data and AI Solutions for Transforming Healthcare: Frameworks, Challenges, and Future DirectionsHouneida Sakly, Ramzi Guetari, Naoufel Kraiem and Mourad Abed5. Scalable Machine Learning for Healthcare: Techniques, Applications, and Collaborative FrameworksAlaa Eddinne ben hmida, Houneida Sakly, Ramzi Guetari and Naoufel Kraiem6. Deployment and Continuous Integration of AI in HealthcareHouneida Sakly, Ramzi Guetari and Naoufel Kraiem7. AI Performance Optimization for HealthcareHouneida Sakly, Ramzi Guetari and Naoufel Kraiem8. Scaling AI Capabilities and Establishing a Roadmap for Sustainable Growth in HealthcareHouneida Sakly, Ramzi Guetari and Naoufel Kraiem9. Governance, Lessons, and Future Trends for Scalable AI in HealthcareHouneida Sakly, Ramzi Guetari, Naoufel Kraiem and Mourad Said