Toward a Machine Learning-Driven Digital Twin for Real-Time Hormone Biosensing in Personalized Infertility Care

Key Points

• This research aims to create a framework for digital twins of biosensors that can provide real-time hormone monitoring.
• Developed a framework for data-driven digital twins of biosensors.
• Integrated digital twins into smart health monitoring systems.
• Focused on personalized infertility care using the digital twin technology.
• Showcased the practicality of digital twin frameworks in hormone biosensing.
• Indicated potential for real-time, adaptive health monitoring.
• Laid the groundwork for precision medicine applications in infertility care.