Analytics is transforming healthcare operations, empowering medical professionals and administrators to leverage data and models to make better decisions. The Analytics Edge in Healthcare provides a practical introduction to this exciting field. The first part of the book establishes the technical foundations of healthcare analytics, spanning machine learning and optimization. The second part of the book presents integrated case studies that cover a wide range of clinical specialties and problem types using descriptive, predictive, and prescriptive analytics. 

Highlighted topics include:

• Predictive models for clinical risk prediction

• Missing data imputation for incomplete medical data

• Natural language processing for study cohort selection

• Computer vision for sarcoma detection

• Multimodal models leveraging electronic health records

• Optimization for hospital capacity planning

• Prescriptive frameworks for treatment personalization

• Fairness in transplantation allocation policy

• A holistic data-driven response to COVID-19