Neuroscience

Neuroradiology datasets hold significant potential for advancing neuroimaging research, yet identifying relevant and up-to-date resources remains challenging. NeuroAIHub is an artificial intelligence (AI)-driven framework designed to automate dataset discovery, improve accessibility, and support structured exploration of neuroradiology datasets. A foundational database was constructed through a multi-reviewer extraction process with standardized metadata harmonization. To maintain and…

The Brain Tumor Reporting and Data System (BT-RADS) standardizes post-treatment MRI response assessment in patients with diffuse gliomas but requires complex integration of imaging trends, medication effects, and radiation timing. This study evaluates an end-to-end multi-agent large language model (LLM) and convolutional neural network (CNN) system for automated BT-RADS classification. A multi-agent LLM system combined…

The Brain Tumor Reporting and Data System (BT-RADS) standardizes post-treatment MRI response assessment in patients with diffuse gliomas but requires complex integration of imaging trends, medication effects, and radiation timing. This study evaluates an end-to-end multi-agent large language model (LLM) and convolutional neural network (CNN) system for automated BT-RADS classification. A multi-agent LLM system combined…

Retinal artery occlusion (RAO) causes sudden, painless, severe vision loss in 1 eye and requires immediate evaluation and management similar to cerebral stroke.