09-07-2025
LG's new AI slashes genetic testing time to under 1 minute
LG AI Research on Wednesday unveiled its next-generation artificial intelligence model, Exaone Path 2.0, which can diagnose diseases by analyzing patients' pathology images alone.
This new AI model is expected to drastically reduce the time required for genetic testing from two weeks to under one minute, marking a step forward in the early diagnosis of diseases such as cancer.
Exaone Path 2.0 has been upgraded from the first edition, trained on higher-quality data. It offers enhanced capabilities in analyzing and predicting genetic mutations, gene expression patterns and subtle structural features within human tissues and cells, the AI research center, affiliated with tech giant LG Group, said.
'Using Exaone Path 2.0, we can reduce the time needed for genetic testing from over two weeks to under one minute,' said Park Yong-min, a lead researcher at LG AI Research.
'Doctors and pharmaceutical companies can quickly analyze pathology images of a patient's tumor tissue, identify which genes have mutated and match them to suitable targeted therapies in real time.'
The latest model has been trained on multiomics data — including DNA and RNA — paired with pathology images, allowing it to understand both cellular structures and underlying biological mechanisms of disease, LG AI Research explained.
As Whole Slide Images often span several gigabytes, AI models typically break them into smaller patches to reduce processing loads. This, however, can lead to 'feature collapse,' where broader structural context is lost.
Exaone Path 2.0 addresses this by learning from both detailed patches and the full-slide view. Trained on over 10,000 WSI-multiomics pairs, it achieves a state-of-the-art 78.4 percent accuracy in predicting genetic mutations, LG explained.
LG also introduced specialized models for diseases such as lung and colorectal cancer, which are designed to help clinicians identify eligible patient groups for targeted therapies while avoiding unnecessary tests.
With the goal of pioneering clinical AI implementation, LG AI Research has partnered with Professor Hwang Tae-hyun and his team at Vanderbilt University Medical Center, one of the top biomedical research institutions in the US.
Together, they aim to develop a multimodal medical AI platform to redefine precision medicine, LG said.
Unlike conventional approaches that first develop technologies and then seek clinical application, the research institute is working on a clinic-first strategy, focusing on solving real-world problems directly within clinical settings for AI development.
'Our goal is not simply to develop a new AI model, but to build an AI platform that can be actively used by medical professionals in real clinical settings to support diagnosis and treatment,' Hwang said.
Hwang is a Korean-American scientist who leads the stomach cancer initiative under the US government's Cancer Moonshot program. He also founded the Molecular AI Initiative at Vanderbilt University Medical Center, where he conducts interdisciplinary research at the intersection of AI and molecular medicine.
With Hwang's team, LG AI Research said it plans to start with oncology and later expand its multimodal AI research into areas such as transplant rejection, immunology and diabetes.
The research institute has also teamed up with the Jackson Laboratory in the US to discover biomarkers and develop treatments for Alzheimer's disease, and it is working with Professor Baek Min-kyung's team at Seoul National University to develop next-generation protein structure prediction AI.
