The Power of Prediction in Health Care

In this comprehensive guide, I offer valuable insights tailored for data science graduate students and early career researchers stepping into the dynamic world of data science.
My distinctive background merges clinical medicine with data science expertise, holding an MBBS, an MBA in Healthcare, and a Ph.D. in Artificial Intelligence in Healthcare. This diverse foundation allows me to bridge the gap between these two fields.
During my early career and Ph.D. journey in data science, I encountered and surmounted the challenges of navigating complex data analysis and machine learning, despite lacking a computer science background. Today, I'm excited to share the knowledge and experiences I've gained with newcomers in the field.
Within the pages of this book, you'll discover a structured, step-by-step approach to conceptualizing, designing, and executing data science projects within the healthcare domain. Tailored for graduate students and early career researchers, this educational journey equips you with practical skills and knowledge to harness the remarkable potential of data science in healthcare.
This book offers:
- A systematic guide for planning and executing data science projects in healthcare.
- A beginner-friendly structure designed to facilitate project development.
- Direct links to valuable resources and open-source tools for creating and executing AI projects in healthcare.
- Access to freely available healthcare databases.
- Real-world case studies illustrating the construction of data science projects.
Whether you're a healthcare professional looking to expand your skill set or a budding data scientist seeking to make a meaningful impact in the healthcare sector, 'The Power of Prediction in Health Care' is an invaluable companion for unlocking the potential of data science in healthcare. Filled with practical examples and actionable advice drawn from real-world scenarios, this book empowers you to make data-driven decisions that enhance patient outcomes and reshape the healthcare landscape.

Rafiq Muhammad has background in healthcare with MBA from SDA Bocconi School of Management, Italy, and holds a Ph.D. in Artificial Intelligence and Machine Learning from Karolinska Institute, Sweden. He has spent the past several years engaging deeply in data analytics and machine learning applications.Rafiq Muhammad is passionate about data science and artificial intelligence and is dedicated to bridging the gap between cutting-edge generative language models and their practical implementations in real life. Rafiq Muhammad has extensive experience in publishing systematic literature reviews in peer-reviewed journals, and teaching and supervising graduate students on how to conduct literature reviews. He also has experience teaching Master Level courses at Karolinska Institute. Rafiq has developed advanced skills in conducting high-quality systematic literature reviews independently (four systematic literature reviews already published and supervised several). During the last 6 years, He has published 10 scientific articles in peer-reviewed academic journals. He has spent the past several years immersing himself in data analytics using artificial intelligence and machine learning, conducting literature reviews, and teaching master-level courses in healthcare. As a medical doctor with expertise in data science, he has the right competence to conceptualize, design, and develop AI applications in healthcare.