Wasswa Shafik – författare

This book provides a comprehensive exploration of how artificial intelligence and digital health innovations are reshaping cancer care across Africa. Beginning with the foundational epidemiological and health system realities of the continent, it examines Africa’s readiness for oncology transformation and the ethical, legal, and social considerations of adopting AI in cancer diagnosis and treatment.

The book presents advanced applications, from deep learning-driven imaging and precision oncology to telepathology, mobile health platforms, and digital tools for survivorship, relapse prediction, and palliative care. It further highlights strategies for scaling AI systems, strengthening rural health infrastructure, fostering public-private partnerships, and building a skilled workforce equipped for the next era of oncology.

Designed as a timely resource for clinicians, cancer researchers, AI scientists, digital health innovators, public health professionals, policymakers, medical educators, and postgraduate students, this work bridges cutting-edge technology with urgent public health needs. It offers actionable frameworks, contextual adaptations for low-resource settings, and a forward-looking vision for equitable, AI-enabled cancer care in Africa. This book serves as both a guide and catalyst for sustainable, inclusive, and technologically empowered oncology systems across the continent.

Wasswa Shafik (Member, IEEE) is a Computer Scientist, Information Technologist, and Educator, serving as Research Director at the Dig Connectivity Research Laboratory (DCRLab), Kampala, Uganda. He earned a Bachelor’s degree in Information Technology from Ndejje University (Uganda), a Master’s in Information Technology Engineering (Communication and Computer Networks) from Yazd University (Iran), and a PhD in Digital Science (Computer Science) from the Universiti Brunei Darussalam (Brunei Darussalam). His research focuses on developing computationally and statistically efficient models and algorithms for complex artificial intelligence and machine learning challenges to support a sustainable future. His interests span Applied AI, Deep Learning, Smart Agriculture, Computer Vision, Digital Health and Education, Ecological Informatics, and Sustainable Computing. Shafik has authored, edited, and co-edited numerous books and published extensively in peer-reviewed journals, book chapters, and IEEE international conferences. He has taught and supported academic programs in Mathematics for Data Science, Advanced Topics in Computing, Advanced Algorithms, and Systems Performance and Evaluation. His professional experience includes roles in research, data management, and leadership across organizations such as PSI, TechnoServe, and Asmaah Charity Organisation.

This book provides a comprehensive exploration of how artificial intelligence and digital health innovations are reshaping cancer care across Africa. Beginning with the foundational epidemiological and health system realities of the continent, it examines Africa’s readiness for oncology transformation and the ethical, legal, and social considerations of adopting AI in cancer diagnosis and treatment.

The book presents advanced applications, from deep learning-driven imaging and precision oncology to telepathology, mobile health platforms, and digital tools for survivorship, relapse prediction, and palliative care. It further highlights strategies for scaling AI systems, strengthening rural health infrastructure, fostering public-private partnerships, and building a skilled workforce equipped for the next era of oncology.

Designed as a timely resource for clinicians, cancer researchers, AI scientists, digital health innovators, public health professionals, policymakers, medical educators, and postgraduate students, this work bridges cutting-edge technology with urgent public health needs. It offers actionable frameworks, contextual adaptations for low-resource settings, and a forward-looking vision for equitable, AI-enabled cancer care in Africa. This book serves as both a guide and catalyst for sustainable, inclusive, and technologically empowered oncology systems across the continent.

Wasswa Shafik (Member, IEEE) is a Computer Scientist, Information Technologist, and Educator, serving as Research Director at the Dig Connectivity Research Laboratory (DCRLab), Kampala, Uganda. He earned a Bachelor’s degree in Information Technology from Ndejje University (Uganda), a Master’s in Information Technology Engineering (Communication and Computer Networks) from Yazd University (Iran), and a PhD in Digital Science (Computer Science) from the Universiti Brunei Darussalam (Brunei Darussalam). His research focuses on developing computationally and statistically efficient models and algorithms for complex artificial intelligence and machine learning challenges to support a sustainable future. His interests span Applied AI, Deep Learning, Smart Agriculture, Computer Vision, Digital Health and Education, Ecological Informatics, and Sustainable Computing. Shafik has authored, edited, and co-edited numerous books and published extensively in peer-reviewed journals, book chapters, and IEEE international conferences. He has taught and supported academic programs in Mathematics for Data Science, Advanced Topics in Computing, Advanced Algorithms, and Systems Performance and Evaluation. His professional experience includes roles in research, data management, and leadership across organizations such as PSI, TechnoServe, and Asmaah Charity Organisation.

The book provides an overview of the challenges and opportunities presented by AI across the insurance value chain. As insurers rapidly integrate machine learning, deep learning, and predictive analytics into underwriting, claims processing, fraud detection, and pricing, the need for robust ethical frameworks and responsible AI governance has become paramount. Algorithmic structures and data pipelines that shape modern insurance systems, that review potential sources of bias, opacity, and inequality are examined. The book addresses technical, legal, and organizational dimensions of ethical AI adoption—ranging from explainability and accountability mechanisms to data privacy, informed consent, and inclusion. The book serves as a foundational guide for developing AI systems in insurance that are not only efficient but also equitable and socially responsible. The book will be invaluable for professionals, scholars, data scientists, actuaries, and policymakers.

Key Features:

The book provides an overview of the challenges and opportunities presented by AI across the insurance value chain. As insurers rapidly integrate machine learning, deep learning, and predictive analytics into underwriting, claims processing, fraud detection, and pricing, the need for robust ethical frameworks and responsible AI governance has become paramount. Algorithmic structures and data pipelines that shape modern insurance systems, that review potential sources of bias, opacity, and inequality are examined. The book addresses technical, legal, and organizational dimensions of ethical AI adoption—ranging from explainability and accountability mechanisms to data privacy, informed consent, and inclusion. The book serves as a foundational guide for developing AI systems in insurance that are not only efficient but also equitable and socially responsible. The book will be invaluable for professionals, scholars, data scientists, actuaries, and policymakers.

Key Features:

This book provides a comprehensive exploration of inclusive, sustainable development, emphasizing the critical need to integrate the perspectives and needs of people with disabilities and marginalized communities into the global sustainability transition to a sustainable future. Through highlighting the intersectionality of identity and the unique challenges faced by these groups, the book addresses a pressing issue: the often-overlooked barriers that hinder their full participation in sustainable transitions. Organized into three parts, the book first contextualizes the relationship between sustainability and inclusion. It delves into the historical and theoretical frameworks that shape our understanding of marginalization, exploring how disability intersects with various social identities. This foundation sets the stage for an in-depth analysis of the United Nations Sustainable Development Goals (SDGs) and the ways in which they can be made more inclusive, ensuring that no one is left behind. The second part identifies and examines the myriad barriers to inclusion within sustainable practices. It addresses structural, socioeconomic, and cultural obstacles that perpetuate exclusion while also critiquing existing policy frameworks for their limitations in addressing the needs of marginalized populations. Through case studies, the book highlights successful initiatives and innovative practices that promote accessibility and equity, mainly through the use of assistive technologies and community engagement. In the final section, the book outlines actionable strategies for fostering inclusive, sustainable development. It emphasizes the importance of community engagement, participatory decision-making, and the empowerment of marginalized voices. Additionally, it discusses metrics for monitoring and evaluating the impact of sustainability initiatives on people with disabilities, providing a framework for accountability and continuous improvement.

This book aims to bridge the gap between sustainability and social justice, offering a roadmap for stakeholders, policymakers, and practitioners committed to creating a more inclusive world.  This book targets academics, policymakers, non-profit societies, and activists working at the intersection of sustainability and social equity and serves as a vital resource for those seeking to understand and promote inclusive practices in the global sustainable transition.