Predictive Analytics in Healthcare, Volume 2

The purpose of this book is to help the reader understand academic entrepreneurship and the steps required to bring more research from the lab to real life, as well as to explore the opportunities of applying generative AI in medical education, such as curriculum development, teaching methodologies, personalized learning, learning assessment, medical program tracking, and medical research. It also presents ten ways how AI can improve the adoption of integrative medicine by discussing some successful case studies. The book also discusses the latest advancements in AI-driven applications across the continuum of the journey of a patient with prostate cancer, from risk assessment and stratification to screening, diagnosis, treatment, and management. It also presents the four most innovative AI-powered solutions that have disrupted precision medicine. Part of IPEM–IOP Series in Physics and Engineering in Medicine and Biology. Key features • Identifies and presents the existing applications of AI in various health specialties so that readers specializing in that field can have a comprehensive overview of tech advancements in their field. • Enables readers to identify what new applications are needed to advance the use of analytics in their field. • Presents case studies for the reader to understand how to bring their ideas to fruition.