NIH’s GeneAgent AI Achieves 92% Accuracy in Reducing AI Hallucinations in Genomic Research
Researchers at the National Institutes of Health (NIH) have unveiled
GeneAgent, a cutting-edge AI-powered tool designed to significantly improve the accuracy of gene set analysis by reducing hallucinations—false or misleading content often produced by large language models (LLMs).
Built atop a powerful LLM, GeneAgent not only generates functional descriptions of biological processes but also fact-checks its own claims against expert-curated databases. This self-verifying mechanism distinguishes it from previous models prone to circular reasoning and overconfidence in inaccurate outputs.
“The AI agent can help researchers interpret high-throughput molecular data and identify relevant biological pathways or functional modules, which can lead to a better understanding of how different diseases and conditions affect groups of genes individually and together,” NIH stated in a press release.
When tested on 1,106 gene sets from known databases, GeneAgent first created functional claims, then ran them through its self-verification engine. Human experts reviewed a sample of 132 claims and found that
92% of the tool’s self-assessments were accurate — marking a notable advance over standard LLMs like GPT-4.
Beyond lab tests, GeneAgent was also applied to real-world datasets from mouse melanoma cell lines. It uncovered potential gene functions that could inform drug discovery for diseases such as cancer.
Source: Originally published at CDO Magazine on August 10, 2025.
Frequently Asked Questions (FAQ)
What is GeneAgent?
GeneAgent is an AI-powered tool developed by researchers at the National Institutes of Health (NIH) designed to improve the accuracy of gene set analysis in genomic research by reducing AI hallucinations.
How does GeneAgent reduce AI hallucinations?
GeneAgent works by first generating functional descriptions of biological processes and then fact-checking these claims against expert-curated databases using a self-verification mechanism.
What was the accuracy rate of GeneAgent?
In tests, GeneAgent achieved 92% accuracy in its self-assessments of functional claims, outperforming standard LLMs like GPT-4.
What are AI hallucinations in the context of genomic research?
AI hallucinations in genomic research refer to false or misleading content that large language models (LLMs) may produce when analyzing complex biological data.
What is the practical application of GeneAgent?
GeneAgent can help researchers interpret high-throughput molecular data, identify relevant biological pathways, and uncover potential gene functions to inform areas like drug discovery, as demonstrated in its application to mouse melanoma cell lines.
Crypto Market AI's Take
The development of GeneAgent by the NIH signifies a critical advancement in the responsible deployment of AI, particularly within complex scientific fields like genomics. The ability of an AI to self-correct and fact-check its outputs is paramount for building trust and ensuring the reliability of AI-driven research. This principle of accuracy and verification is also fundamental in the financial markets, where our platform,
Crypto Market AI, leverages advanced AI agents to provide precise market analysis and trading strategies. Ensuring that AI models are grounded in verifiable data and capable of self-assessment is key to mitigating risks and unlocking the true potential of artificial intelligence in both scientific discovery and financial innovation. Our commitment to accuracy extends to our
AI Agents section, which details how various AI agents are being developed to tackle complex problems across different industries.
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