Optimized Predictive Models in Health Care Using Machine Learning
by Sandeep Kumar, Anuj Sharma, Navneet Kaur, Lokesh Pawar, Rohit Bajaj
Preface
This book provides more relevant information on optimized predictive models in healthcare using machine learning. As a resource for students, academics, and researchers from the industry who wish to know more about real-time applications, it focuses on how humans and computers interact to ever-increasing levels of complexity and simplicity. The book provides content on the theory of optimized predictive model design, evaluation, and user diversity. Going beyond descriptions of rehabilitation methods for specific processes, it explains the underlying causes of the social and organizational problems. This book describes new algorithms for modeling that are now accessible to scientists of all varieties. The healthcare industry faces an unprecedented challenge to provide efficient and cost-effective care while maintaining high patient satisfaction. Predictive modeling, a field of machine learning, has emerged as a powerful tool in healthcare for identifying high-risk patients, predicting disease progression, and optimizing treatment plans. By leveraging data from various sources, predictive models can help healthcare providers to make informed decisions, resulting in better patient outcomes and reduced costs. This book offers a comprehensive guide to developing and implementing optimized predictive models in healthcare and is intended for healthcare professionals, data scientists, and researchers interested in using predictive modeling to improve patient care and outcomes. ...