By integrating patient data with sophisticated algorithms, dynamic surrogate models provide clinicians with invaluable insights, enabling personalized and proactive healthcare delivery. This article explores the role of dynamic surrogate models in patient monitoring and treatment optimization, highlighting their benefits, challenges and future prospects. Dynamic surrogate models are emerging as powerful tools in healthcare for patient monitoring and treatment optimization. These models leverage advanced computational techniques to simulate patient physiology, predict disease progression and optimize treatment strategies in real-time.
HTML PDFShare this article
Global Journal of Technology and Optimization received 847 citations as per Google Scholar report
