Company Filing History:
Years Active: 2024
Title: Lishan Feng: Innovator in Lifelong Machine Learning for Healthcare
Introduction
Lishan Feng is a prominent inventor based in Philadelphia, PA, known for his groundbreaking work in the field of machine learning. He has made significant contributions to healthcare technology through his innovative approaches to data analysis and patient identification.
Latest Patents
Lishan Feng holds a patent for a "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 to improve prediction performance. The outputs from each component of the framework are fed into a wide and shallow neural network. The posterior structure of the final model output may be utilized as a prior structure when the deep learning model is refreshed with new data. Lifelong learning is implemented by dynamically integrating present learning from the wide and deep learning components with past learning from traditional tree models in the prior component into future predictions. This innovative model increases accuracy in identifying patient profiles by continuously learning as new data become available, without forgetting prior knowledge.
Career Highlights
Lishan Feng is currently employed at IQVIA Inc., where he continues to develop and refine his machine learning models. His work focuses on enhancing the accuracy and efficiency of patient identification processes in healthcare settings.
Collaborations
Lishan has collaborated with notable colleagues, including Guanhao Wei and Yunlong Wang, to advance research and development in machine learning applications for healthcare.
Conclusion
Lishan Feng's contributions to the field of lifelong machine learning represent a significant advancement in healthcare technology. His innovative approaches are paving the way for more accurate patient identification and improved healthcare outcomes.