CBMI@UTHSC provide the researchers, and clinicians with customized biomedical and clinical informatics applications to help manage complex translational and clinical research needs and gain insights into various diseases and conditions.

In the past, we have developed an open source software for online feature extraction and machine learning pipeline for real-time analysis of streaming physiological data. We have also built machine learning and deep learning models to predict fever, sickle cell disease, and sepsis in children and adults.

Through the Google Summer of Code (GSoC) program, we are specifically interested in creating open-source web application to identify the onset of abnormal conditions using the large-scale real-time sensor data at the bed-side.