CARE-AD: a multi-agent large language model framework for Alzheimer's disease prediction using longitudinal clinical notes
These videos have been matched automatically. Contact us if they are not relevant.
These videos have been matched automatically. Contact us if they are not relevant.
View abstract on PubMed
Summary
This summary is machine-generated.A new multi-agent large language model (LLM) framework, CARE-AD, shows promise for predicting Alzheimer's disease (AD) onset using electronic health records. This approach improves early AD risk assessment accuracy compared to single-model methods.
Area Of Science
- Artificial Intelligence in Medicine
- Computational Neuroscience
- Clinical Informatics
Background
- Large language models (LLMs) demonstrate potential across various fields but have limited application in complex clinical prediction.
- Early prediction of Alzheimer's disease (AD) is crucial for timely intervention and management.
Purpose Of The Study
- To introduce CARE-AD, a novel multi-agent LLM framework for forecasting Alzheimer's disease onset.
- To evaluate the efficacy of CARE-AD in analyzing longitudinal electronic health record (EHR) notes for early AD risk assessment.
Main Methods
- Developed CARE-AD, a framework utilizing specialized LLM agents for extracting AD-relevant signs and symptoms from EHR notes.
- Emulated a collaborative diagnostic process by assigning domain-specific evaluation tasks to individual LLM agents.
- Conducted a retrospective evaluation comparing CARE-AD against baseline single-model approaches.
Main Results
- CARE-AD achieved higher accuracy (0.53) in predicting AD risk 10 years prior to diagnosis compared to baseline models (0.26-0.45).
- The multi-agent system demonstrated superior performance in analyzing longitudinal EHR data for AD risk forecasting.
Conclusions
- Multi-agent LLM systems are feasible for supporting early Alzheimer's disease risk assessment.
- CARE-AD's performance highlights the potential of integrating advanced AI into clinical decision support workflows for neurodegenerative diseases.
These videos have been matched automatically. Contact us if they are not relevant.
These videos have been matched automatically. Contact us if they are not relevant.
Related Concept Videos
Alzheimer's Disease (AD) is a continually advancing neurodegenerative disorder, distinguished by escalating memory loss, cognitive dysfunction, and dementia. The disease unfolds in three stages: preclinical, mild cognitive impairment (MCI), and dementia. Its onset is insidious, and the progression gradual, with the cause not well explained by other disorders.
The clinical diagnosis of AD hinges on the presence of memory and other cognitive impairments. Biomarkers, such as changes in Aβ...
Alzheimer's Disease (AD), a neurodegenerative disorder, is pathologically identified by amyloid plaques and neurofibrillary tangles composed of tau protein. AD pharmacotherapy aims to manage cognitive symptoms, delay disease progression, and treat behavioral symptoms. The treatment is primarily symptomatic and palliative, with no definitive disease-modifying therapy available. Cholinesterase inhibitors, including donepezil (Aricept), rivastigmine (Exelon), and galantamine (Razadyne), are...