Artificial Intelligence-Enabled Blockchain Technology and Digital Twin for Smart Hospitals

21Advancing Healthcare Diagnostics: Machine Learning–Driven Digital Twins for Precise Brain Tumor and Breast Cancer Assessment

J. Olalekan Awujoola^1*, T. Aniemeka Enem², F. N. Ogwueleka³, O. Abioye¹ and E. Abidemi Awujoola¹

¹Nigerian Defence Academy, Kaduna State, Nigeria

²Airforce Institute of Technology, Kaduna State, Nigeria

³University of Abuja, Abuja, Nigeria

Abstract

This study delves into the unexplored terrain of machine learning–driven digital twins, aiming to revolutionize brain tumor and breast cancer diagnostics while integrating the concept of smart hospitals. Unlike previous research that primarily focused on either brain tumor recognition or breast cancer diagnosis, this investigation pioneers the development of specialized digital twins capable of concurrently addressing both healthcare challenges. Leveraging advanced machine learning models, notably MobileNetV2 with enhanced attention mechanisms, the study meticulously crafts and trains digital twins tailored for MRI image analysis in oncology. These digital replicas undergo rigorous validation before being applied to MRI images for precise classification and diagnostic assessments. The research findings highlight the significant potential of machine learning–enabled digital twins in transforming diagnostic accuracy and treatment strategies within the context of smart hospitals. This pioneering approach not only enhances the capabilities of healthcare providers but also fosters a new era of personalized and ...