Medical AI
This research creates AI tools that help doctors and medical staff with
tasks like summarizing records or explaining medical information.
We train both large and small language models using medical data and expert advice to make sure they are correct and safe.
The goal is to support medical professionals and improve patient care.
Dongryul Oh, Sujin Kang, Heejin Kim, and Dongsuk Oh
Applied Sciences 15.5 (2025): 919–933
Small language models (SLMs) are increasingly utilized for on-device applications due to their ability to ensure user privacy, reduce inference latency, and operate independently of cloud infrastructure. However, their performance is often limited when processing complex data structures …
Keywords:
small language model (SLM), on-device AI, graph neural network (GNN), graph transformer, graph convolutional network (GCN) …
Dongsuk Oh, Jonghyeon Moon, Kyoungtae Park, Wonjun Kim, Seungho Yoo, Hyungwoo Lee, and Jiho Yoo
Expert Systems with Applications 249 (2024): 123620
With the increase in the aging population of many countries, the prevalence of neovascular age-related macular degeneration (nAMD) is expected to increase. Morphological parameters such as intraretinal fluid (IRF), subretinal fluid (SRF), subretinal hyperreflective material (SHRM) …
Keywords:
Graph convolution network, Transformer, Multiscale skip connection, Medical image segmentation, Retinopathy