Department:  Mechatronics Engineering

The workshop in brief:

A workshop was held to discuss recent advances in AI-based Alzheimer’s disease diagnosis, focusing on the integration of Vision Transformers (ViTs) and Large Language Models (LLMs). The presented framework uses ViTs to classify brain MRI scans into Normal Control, Mild Cognitive Impairment, and Alzheimer’s Disease, while LLMs generate clear and clinically meaningful diagnostic reports. Discussions highlighted the advantages of transformer-based models over CNNs, as well as the importance of explainability and ethical considerations in healthcare AI. The workshop concluded that combining ViTs and LLMs is a promising approach for early diagnosis and clinical decision support.

Participants:  27

Place: Tishk International University, Education Building 302

Session topics: 

The workshop successfully demonstrated the effectiveness of integrating Vision Transformers and Large Language Models for Alzheimer’s disease diagnosis and automated reporting. The proposed approach showed strong potential for improving diagnostic accuracy, enhancing interpretability, and supporting clinical decision-making. Participants identified key future directions, including the adoption of explainable AI techniques, ethical deployment in healthcare, and validation using real-world clinical data.