Like predictive modeling, detecting positive COVID-19 cases with technology – most notably, CT scans and chest X-rays – is in high demand. Additionally, AI has proven useful and effective for mass screenings of conditions across the medical field. Morvan has been researching this effectiveness and AI’s role in medical studies.

“Without AI-guided tools, technological advances in biomedical and health care informatics may not be possible,” he said.

Morvan conducted tests and observations using deep learning models, which are technological systems trained to identify certain patterns or objects as the human brain does. Deep learning models are useful for both the diagnosis and prognosis of various illnesses, such as COVID-19.

At the end of the research process, Morvan concluded that his tests were mostly successful in detecting a positive COVID-19 case. The accuracy reached a maximum of 63% on the validation set of his deep learning model and a maximum of 65.4% on the training set.

“In the future, this project could be combined with other well-known deep learning models, such as chest X-rays, to employ multimodal learning and representation for COVID-19 screening,” said Morvan.

Morvan, an international student from Meucon, France, said he was inspired to pursue his research topic by Josh Henderson, a current graduate student and adjunct professor for the Department of Computer Science at USD. “I remember talking to Henderson about his project for detecting COVID-19 using chest X-rays,” said Morvan. “I thought it would be pretty cool if I could do something similar with my research.”

During his first research experience this past summer at the UDiscover Summer Scholars Program, Morvan was motivated to begin studying AI and deep learning models. It was here that he received the support and funding necessary to conduct his research.

“One of the challenges of my research project was that I was a beginner in programming with very little experience in AI,” said Morvan. “I learned a lot during the UDiscover internship, and this knowledge will be very useful for the future.”

Morvan recently received an Undergraduate Research Excellence Award for his research contributions and was nominated for the award by KC Santosh, Ph.D., chair of the Department of Computer Science.

“As an undergraduate student, Morvan has shown his amazing talent in data collection, research review, implementation, and writing scientific reports,” said Santosh. “He is a hardworking scholar with a commendable research attitude.”

After graduation, Morvan plans to return to Europe and pursue a master’s degree in artificial intelligence and machine learning. “I would like to work in the domain of AI and computer vision,” he said. “I am already excited for this new chapter of my life.”

Press Contact
Hanna DeLange
Contact Email
Contact Website website