People use the Internet to diagnose themselves—Can this UMBC student’s work help moderate medical content on the web?

Sun, 17 Aug 2025 17:22:27 -0400
ai, health, misinformation, online, research, umbc

In 2024, information systems Ph.D. student Ommo Clark penned an opinion piece for BusinessDay Nigeria exploring why many Nigerians diagnose and treat their medical conditions themselves, often turning to unreliable online information.

While the essay was inspired by firsthand experiences in her native country, the impulse to consult “Dr. Google” is a worrying global trend, Clark says, and one that has motivated her Ph.D. work. It’s unlikely that people will stop going online with health questions, so Clark is researching ways that AI could help patients, healthcare providers, public health officials, and content platforms better understand and evaluate the sea of medically related content on the Internet.

Ommo’s efforts were recently recognized when one of her research papers, co-authored with information systems professor Karuna Joshi, won the Best Student Paper Award at the IEEE International Conference on Digital Health 2025, held in July in Helsinki, Finland. The paper, titled “Real-Time Detection of Online Health Misinformation using an Integrated Knowledgegraph-LLM Approach,” describes the results of combining two types of AI approaches to tackle the problem of identifying online health misinformation.

Read more about their work in this UMBC News article.