ECE & COVID-19 Research
Hespanha and Manjunath contribute to the worldwide fight against the Coronavirus
ECE Professor Joao Hespanha and his Networked Control Laboratory are developing tools to inform and advise decision making for control of large-scale global pandemics. Key goals of the project include making reliable predictions for the state of a pandemic in the next few days/weeks/months, estimating effects of governmental measures in the dynamics of the pandemic, and designing protocols for effective control of a pandemic to prevent overloading the healthcare system. A key feature of his work has to do with “annotating” predictions/estimates/protocols with quantitative measures of uncertainty so decision makers can explore realistic best-case and worst-case scenarios.
Researchers in the Vision Research Laboratory, UCSB, in collaboration with Santa Barbara Cottage Hospital, are working on an AI paradigm that will identify characteristic differences in Computated Tomography (CT) scans between COVID-19 and other similar types of viral pneumonia. Dr. Ashutosh Shelat, radiologist at Cottage Hospital and collaborator on this project, notes distinguishing other viral pneumonia from COVID-19 is difficult, even for experts, and can lead to nonspecific recommendations and diagnosis. S. Shailja, a graduate student in ECE, and Manjunath, ECE Chair and Director of the Center for Multimodal Big Data Science and Healthcare, are building computer vision models to detect characteristic signatures in lung CT scans of COVID-19 patients. In addition to aiding radiologists in diagnostic differences between COVID-19 and other viral pneumonia, this research will focus on differentiating the U.S. demographic from other worldwide sources and thus remove concerns of genetic drift of SARS-CoV2 over its progression. Methods developed will be available online using the UCSB BisQueMD web portal.
The ECE Current "ECE COVID-19 | Recent Research" (Fall 2020 page 16)