Company Filing History:
Years Active: 2024
Title: Frank Jing - Innovator in Lifelong Machine Learning for Healthcare
Introduction
Frank Jing is a prominent inventor based in Beijing, China. He has made significant contributions to the field of healthcare through his innovative work in machine learning. His expertise lies in developing advanced algorithms that enhance patient care and improve healthcare outcomes.
Latest Patents
Frank Jing holds a patent for a groundbreaking invention titled "Lifelong machine learning (LML) model for patient subpopulation identification using real-world healthcare data." This deep learning model implements continuous, lifelong machine learning based on a Bayesian neural network. It utilizes an inventive framework that includes wide, deep, and prior components, employing diverse algorithms to leverage available real-world healthcare data differently. The model aims to improve prediction performance significantly. The outputs from each component are integrated into a wide and shallow neural network, allowing the model to refresh with new data while retaining prior knowledge. This innovative approach increases accuracy in identifying patient profiles by continuously learning as new data becomes available.
Career Highlights
Frank Jing is currently employed at IQVIA Inc., where he applies his expertise in machine learning to advance healthcare solutions. His work focuses on integrating real-world data into predictive models, which enhances the ability to identify patient subpopulations effectively. His contributions have been instrumental in bridging the gap between technology and healthcare.
Collaborations
Frank has collaborated with notable colleagues, including Guanhao Wei and Yunlong Wang. Their combined efforts have led to significant advancements in the application of machine learning in healthcare.
Conclusion
Frank Jing's innovative work in lifelong machine learning represents a significant advancement in healthcare technology. His contributions are paving the way for more accurate patient identification and improved healthcare outcomes.