BRAINS: A Retrieval-Augmented System for Alzheimer's Detection and
  Monitoring
As the global burden of Alzheimer's disease (AD) continues to grow, early and
accurate detection has become increasingly critical, especially in regions with
limited access to advanced diagnostic tools. We propose BRAINS (Biomedical
Retrieval-Augmented Intelligence for Neurodegeneration Screening) to address
this challenge. This novel system harnesses the powerful reasoning capabilities
of Large Language Models (LLMs) for Alzheimer's detection and monitoring.
BRAINS features a dual-module architecture: a cognitive diagnostic module and a
case-retrieval module. The Diagnostic Module utilizes LLMs fine-tuned on
cognitive and neuroimaging datasets -- including MMSE, CDR scores, and brain
volume metrics -- to perform structured assessments of Alzheimer's risk.
Meanwhile, the Case Retrieval Module encodes patient profiles into latent
representations and retrieves similar cases from a curated knowledge base.
These auxiliary cases are fused with the input profile via a Case Fusion Layer
to enhance contextual understanding. The combined representation is then
processed with clinical prompts for inference. Evaluations on real-world
datasets demonstrate BRAINS effectiveness in classifying disease severity and
identifying early signs of cognitive decline. This system not only shows strong
potential as an assistive tool for scalable, explainable, and early-stage
Alzheimer's disease detection, but also offers hope for future applications in
the field.
690ae401d70e173c84529063
Rajan Das Gupta
claimed_verified
2025-11-20T08:50:25.347Z
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Rajan Das Gupta
rajandasgupta
user
rajandasgupta
690ae401d70e173c84529064
Md Kishor Morol
claimed_verified
2026-01-02T15:41:05.099Z
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https://cdn-avatars.huggingface.co/v1/production/uploads/1648633728027-614b767b3157900de3aeae9b.jpeg
Md Kishor Morol
kishormorol
user
kishormorol
690ae401d70e173c84529065
Nafiz Fahad
690ae401d70e173c84529066
Md Tanzib Hosain
690ae401d70e173c84529067
Sumaya Binte Zilani Choya
690ae401d70e173c84529068
Md Jakir Hossen
BRAINS: A Retrieval-Augmented System for Alzheimer's Detection and
  Monitoring
As the global burden of Alzheimer's disease (AD) continues to grow, early and
accurate detection has become increasingly critical, especially in regions with
limited access to advanced diagnostic tools. We propose BRAINS (Biomedical
Retrieval-Augmented Intelligence for Neurodegeneration Screening) to address
this challenge. This novel system harnesses the powerful reasoning capabilities
of Large Language Models (LLMs) for Alzheimer's detection and monitoring.
BRAINS features a dual-module architecture: a cognitive diagnostic module and a
case-retrieval module. The Diagnostic Module utilizes LLMs fine-tuned on
cognitive and neuroimaging datasets -- including MMSE, CDR scores, and brain
volume metrics -- to perform structured assessments of Alzheimer's risk.
Meanwhile, the Case Retrieval Module encodes patient profiles into latent
representations and retrieves similar cases from a curated knowledge base.
These auxiliary cases are fused with the input profile via a Case Fusion Layer
to enhance contextual understanding. The combined representation is then
processed with clinical prompts for inference. Evaluations on real-world
datasets demonstrate BRAINS effectiveness in classifying disease severity and
identifying early signs of cognitive decline. This system not only shows strong
potential as an assistive tool for scalable, explainable, and early-stage
Alzheimer's disease detection, but also offers hope for future applications in
the field.
BRAINS, a system using Large Language Models, effectively detects and monitors Alzheimer's disease by integrating cognitive assessments and case retrieval.
Large Language Models cognitive diagnostic module case-retrieval module latent representations Case Fusion Layer clinical prompts Alzheimer's risk disease severity cognitive decline