Better Hospital Care Through Machine Learning Possible as ABA Student, Professor Put Analytics to Work
The scheduling and coordination of patient care between hospital nurses stands to become much easier thanks to the enterprising research of MS in Applied Business Analytics candidate Yuzhen Liang.
In their recent blog post, “Application of Machine Learning to Real Time Nurse Dispatching,” Liang and BU MET Associate Professor of the Practice John Maleyeff share the progress they have made in their efforts to use data science and machine learning to help nurses provide timely and informed patient care in busy hospital wards. Their interdisciplinary study, conducted in collaboration with the Grand Valley State University School of Nursing, involved collecting data from experienced nurses on the complex intricacies of managing the needs of multiple patients and developing machine learning algorithms to produce a scheduling system that can help improve patient outcomes and deliver medical services to underserved populations.
A master’s student in applied business analytics, Liang works as a data research assistant with the University and as a database and administration intern with Dekra Services Inc., where she works to design user-friendly decision modeling and data analytics programs for her colleagues and clients.
Learn more at BU’s Institute for Health System Innovation & Policy, which brings together the broad and deep capacities of Boston University to provide value in addressing the challenges of the health sector in the United States and globally.