Primary supervisor
Trang VuCo-supervisors
- Thanh Nguyen (NMHS)
Manual medical report writing is time-consuming and subject to variability. Recent advances in large language models (LLMs) create new opportunities for automating this process. This project explores using LLMs to generate medical reports from a very large dataset, aiming to streamline workflows and support clinical decision-making. Students will work on data preprocessing, model fine-tuning, and performance evaluation, contributing to advances in medical AI.
Student cohort
Double Semester
Aim/outline
- Develop data construction and preprocessing pipeline
- Fine-tune and evaluate an LLM for medical report generation
- Compare generated reports with expert annotations
- Investigate challenges and propose improvements
- An open source code and possibly a publication in medical AI/NLP venues
URLs/references
- Varol Arısoy, M., Arısoy, A. & Uysal, İ. A vision attention driven Language framework for medical report generation. Sci Rep 15, 10704 (2025) https://www.nature.com/articles/s41598-025-95666-8
- Chen, Qi, et al. "A survey of medical vision-and-language applications and their techniques." arXiv preprint arXiv:2411.12195 (2024). https://arxiv.org/abs/2411.12195
Required knowledge
- Good Python programming
- Interest in AI/ML with prior deep learning experience
- Familiarity with medical imaging is a plus but not required