A Vision-Language Foundation Model for Brain Disease Diagnosis From Multimodal Data
The goal of this observational study is to develop an innovative, comprehensive, and explainable AI vision-language foundation model (VLM) to advance the diagnosis and interpretation of brain diseases using multi-modal data. We will include patient demographics, medical imaging data (such as MRI, CT, and PET scans), histopathological data, genomic data when available, and other necessary laboratory examinations and tests to establish a screening and diagnostic model for brain diseases.
Patients with brain tumors were pathologically diagnosed. [+3]
Cases in which MRI were incomplete or with significant noise and artifacts.