A team of Georgia Tech and Emory University researchers are exploring how artificial intelligence (AI) can be used to improve diagnoses and treatment of diseases.
A specific type of AI, called natural language processing (NLP), can be used to speed up the time between a patient-initiated message, a physician response, and access to COVID-19 antiviral treatment, according to a study recently published in JAMA Open Network.

Prof. May Wang
May Wang, PhD, a co-author on the study, professor and Wallace. H. Coulter Distinguished Faculty Fellow, said the study showed the power of using AI to rapidly process and alert clinical teams on which patients are at higher risk for COVID-19 and require further screening.
"The results of our study illustrated the power of using advanced NLP models in accurately identifying patients at risk of a certain disease (in this case, COVID-19) in real time. It showed that the speed for patient access to healthcare can be significantly increased," Wang explained. "That is, instead of relying on human experts (nurses or physicians) to manually process the patient messages, the NLP models can automatically process the information and alert the clinical team on which patients are at higher risk and require further screening."
Latest BME News
New research from Georgia Tech helps doctors predict how therapies will interact with a child's immune system, potentially improving outcomes and reducing risks.
Georgia Tech researchers reveal the dynamic role of inhibitory neurons in spatial memory and learning
The department remains a top-ranked biomedical engineering program for graduate education in the nation.
Neuroscientist and former BME grad student Nuri Jeong is helping to reshape lives and careers
Georgia Tech authors reflect a rapidly evolving field in new edition highlighting real-world applications
Hands-on approach to teaching microfluidics is inspiring future innovators
In this edition of Ferst Exchange, Coulter BME's Aniruddh Sarkar explains the science.
Georgia Tech researchers uncover the role of lateral inhibition in enhancing contrast and filtering distractions, with implications for neuroscience and AI.