arXiv:2602.11460v2 Announce Type: replace Abstract: Large language models (LLMs) have shown great potential for healthcare applications. However, existing evaluation benchmarks provide minimal coverage of Alzheimer's Disease and Related Dementias (ADRD). To address this gap, we introduce ADRD-Bench, a preliminary ADRD-specific LLM benchmark. ADRD-Bench has two components: 1) ADRD Unified QA, a synthesis of 1,438 questions consolidated from seven established medical benchmarks, providing a unified assessment of clinical knowledge; and 2) ADRD Caregiving QA, a novel set of 149 questions derived
The rapid advancement and application of LLMs in healthcare necessitates specialized benchmarks to ensure their safe and effective deployment in critical areas like Alzheimer's research.
A specialized benchmark for ADRD will accelerate the development of reliable AI tools for diagnosis, research, and patient care, impacting an increasingly prevalent global health challenge.
The availability of ADRD-Bench provides a standardized framework for evaluating LLMs, directly influencing the quality and trustworthiness of AI applications in neurodegenerative disease. This will likely push for more specific benchmarks in many other areas of medicine.
- · AI developers in healthcare
- · Alzheimer's researchers
- · Patients with ADRD
- · Medical AI ethics committees
- · Generic LLM benchmarks
- · Unspecialized medical LLM tools
LLMs can now be more rigorously tested for their knowledge and utility regarding Alzheimer's Disease and Related Dementias.
Improved LLM performance in ADRD could lead to more accurate early diagnosis and personalized care strategies.
The success of this specialized benchmark might spur the creation of similar, highly specific benchmarks for other complex medical conditions, accelerating AI adoption in diverse healthcare fields.
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