Grant Awarded to Research the use of AI and Data Science in Predicting and Preventing Disease

Mark Chapman, assistant professor of integrated engineering, recently received an NSF grant to help further research on developing advanced artificial intelligence (AI) and data science tools aimed at understanding, predicting and preventing disease. This grant award, totaling $488,222, will fund eight undergraduate students per year over three years from institutions in the U.S., including the University of San Diego (USD), to conduct research in Stockholm, Sweden. 

Technological advancements in microscopy, medical imaging and within the -omics space have resulted in an expansion of big data within biology and health in recent decades. With the escalating availability of these large datasets, new challenges are arising related to the analysis and interpretation of these data. 

“We are turning to artificial intelligence and data science techniques to mine data in order to maximize our understanding of various biological systems,” explains Chapman, who leads the biomedical engineering concentration program at USD. “Although significant advances have been made in this area, new AI and data science methods are needed as existing biotechnologies improve and new methods emerge, which will increase the volume and complexity of the datasets we are dealing with.”

The development of these new methods requires the creation of educational programs to train the next generation of AI and data scientists. Given this need, this International Research Experiences for Students (IRES) project provides a unique opportunity for undergraduate students to conduct summer research abroad for 10 weeks with world-renowned researchers at the Karolinska Institute and Science for Life Laboratory in Stockholm, Sweden. 

“The projects students will be involved in are at the forefront of biomedical data science and have the potential to deepen our knowledge of fundamental biology by contributing to our understanding of disease mechanisms, as well as examining the preventive medicine capabilities of physical activity,” says Chapman. “Additionally, some research students will be involved in the development of new computational tools that could contribute to the identification of early disease detection methods related to patterns discovered using AI-facilitated radiology/pathology techniques.”

The program emphasizes providing research experiences, training and mentorship for underrepresented racial minorities and women. 

“Improving diversity in STEM is critical to ensuring an equitable future, especially in the context of this proposal since racial and gender biases are known to exist within AI algorithms.” Chapman implores, “Without a concerted effort to increase diversity in the fields of AI and data science, there is a risk of further exacerbating the biases embedded in AI.”

The student researchers will also participate in activities outside of the lab to help them understand the broader impact of their work. One example is the AI and Health Open Forum portion of this IRES program that will bring students, scientists, policy makers and the public together to discuss AI innovations aimed at improving health. During this event, the societal and ethical implications of this work will also be discussed.

 “I believe there is a misconception about how AI is 'scary' and that robots are taking over the world, but applying AI to medical contexts has great potential to help people,” says Chapman. “Overall, the research theme of this grant is inherently tied to improving the health of people in society by generating scientific knowledge and developing technologies that can assist in medical diagnoses and help with early detection of disease — an extremely effective way to drive down mortality.”

— Michelle Sztupkay